Intertemporal Risk Management Decisions of Farmers under Preference, Market, and Policy Dynamics



We use the fitted linear time trend model to simulate annual wheat yields in Whitman
County, and use the fitted stochastic trend models to simulate Grant County yield, Portland Cash
price, and CBOT futures price. An empirical distribution with 2000 samples is simulated for
each of the next five years and for each series. All the series are first simulated independently
without autocorrelations or contemporaneous correlations. For the cash and futures prices, we
then impose a correlation of 0.871 based on historical data. Table 2 gives the descriptive
statistics of the simulated data.

Parameter Calibration

Identification of farmers’ risk preferences and time preferences has been attempted in
previous studies using different models (Saha, Shumway and Talpaz, 1994; Chavaz and Holt,
1996; Epstein and Zin, 1990; Lence, 2000). Among them, Lence used a similar dynamic GEU
model to estimate US farmers’ preference parameters based on aggregated consumption and
asset return data from 1966-1994. We implement those estimates,
α= -0.13 , β= 0.89 and
ρ= 0.9493, as the base for our representative farmers and assume they stay fixed over time.

In the determination of current consumption (or net income) level, transportation cost
between the Portland spot market and the two counties is set at $0.50 per bushel for Whitman
County and $0.47 for Grant County; production cost is determined as $203 per acre for Whitman
County (Hinman and Baldree, 2004) and $195 for Grant County6; transaction cost associated
with hedging is set at $0.017/bushel. The price used to indemnify crop loss in the insurance
programs is the CBOT September wheat futures price plus a Portland basis of $0.45 per bushel.
The insurance coverage levels are restricted to be either zero or from 50% to 85% with an
increment of 5%. The insurance premium is computed as the product of the expected indemnity

6 Production cost for Grant County is derived based on budgeting report for Lincoln County, a similarly
dry county in Washington State. Reference: Esser, Hinman, and Platt (2003).

14



More intriguing information

1. The name is absent
2. CGE modelling of the resources boom in Indonesia and Australia using TERM
3. Nonparametric cointegration analysis
4. How to do things without words: Infants, utterance-activity and distributed cognition.
5. The name is absent
6. The Effects of Reforming the Chinese Dual-Track Price System
7. Real Exchange Rate Misalignment: Prelude to Crisis?
8. The name is absent
9. The name is absent
10. The name is absent
11. Integrating the Structural Auction Approach and Traditional Measures of Market Power
12. The Employment Impact of Differences in Dmand and Production
13. The name is absent
14. Regulation of the Electricity Industry in Bolivia: Its Impact on Access to the Poor, Prices and Quality
15. The name is absent
16. Imperfect competition and congestion in the City
17. The Value of Cultural Heritage Sites in Armenia: Evidence From a Travel Cost Method Study
18. Delivering job search services in rural labour markets: the role of ICT
19. Segmentación en la era de la globalización: ¿Cómo encontrar un segmento nuevo de mercado?
20. Monetary Discretion, Pricing Complementarity and Dynamic Multiple Equilibria