Dairy Yield Risk

1. Dairy Yield Risk Joshua D. Woodard Assistant Professor of Agribusiness and Finance Zaitz Family Sesquicentennial Faculty Fellow Dyson School of Applied Economics and Management Cornell University Jing Yi Postdoctoral Research Associate Dyson School of Applied Economics and Management Cornell University Jenny Ifft Assistant Professor Mueller Family Sesquicentennial Faculty Fellow Dyson School of Applied Economics and Management Cornell University August, 2017 AAEA Annual Meeting, Chicago

2. Introduction • Extensive literature exists on • modeling milk prices and feed margins • modeling crop yields • Very little on farm level dairy yields • Often assumed that there is no (or trivial yield risk), on basis of state level yield records • Virtually all available risk management tools for dairy focus on either milk prices or milk over feed cost margins. • Purpose: investigate farm level dairy yield and revenue risk and distribution form • Important given current policy environment and discussions

3. Questions and Overview • What is the distributional form for dairy yields? • What is relationship to state level yields (i.e., what is systematic risk of farm to state)? • Use farm level data from 1993-present from New York Dairy Farm Business Summary (DFBS) • Counter to conventional wisdom, results suggest: • farm-level milk yield risk is fairly substantial, and • systemically related to state-level milk yields • There is a great deal of heterogeneity across farms in terms of level of sensitivity to state level risk and productivity

4. Current Policy Environment • Risk management policy and options for dairy are all: • Exclusively price based (no yield or revenue protection) • Rely on national level prices, not state level (basis risk) • Previous Farmbill: Milk Income Loss Contract (MILC): National level price with a feed trigger • Current Dairy Title: Dairy Margin Protection Program (MPP): Explicit margin insurance like program written on national level margin • LGM: Longstanding margin insurance program offered through RMA (uses class III futures) • Dairy Revenue Protection (Dairy RP): Prospective program being developed by American Farm Bureau ([public info]) • Disclaimer: Woodard is the contracted developer

5. Data • Farm level data from New York Dairy Farm Business Summary (DFBS), 1993-present • Analysis focuses on farms with 15>years of data (F=100) • Frequency: Annual data • Units: $/cwt for price and cwt./cow for yield • State level yield, price, and revenue from National Agricultural Statistics Service QuickStats dataset, obtained via Ag-Analytics.Org

6. Methods • Distribution analyses • Detrend all farms (state-level and farm level) • Pool into three risk groups: Anderson Darling (AD) tests • Farm-by-Farm AD Test • Farm-to-Farm KS 2 Sample Tests • State Level Sensitivity Regressions • Yield • Revenue • Revenue by Production System

10. Methods

11. Detrended Yield and Fitted Distibutions

13. Table presents 2 Sample Kolmogrov Smirnov test of each farm against each other farm (detrended), the frequency of rejecting the Null (null is that distributions are the same).

16. Distribution of Farm-State Sensitivities (i.e., CAPM type betas)

18. Conclusion • Fairly substantial yield risk at the farm level (after accounting for trend) • For highest (lowest) risk 1/3rd farms, +/- 15% (10%) yield swings are not unusual • Generally, normal distribution can not be rejected, performed best compared to 3 other distributions (Weibull, Log-Normal and Extreme Value) • Farm yields and revenues systematically related to state yields and revenues • There is a great deal of heterogeneity across farms in terms of level of sensitivity to state level risk and productivity, this is in large part due to production systems and scale.