Forward hedging under price and production risk of wheat

Abstract

This paper estimates optimal hedging ratios for a Finnish spring wheat producer under price and yield uncertainty. The contract available for hedging fixes the price and quantity at the time of sowing for a delivery at harvest. Autoregressive models are used to obtain point forecasts for the conditional mean price and price volatility at harvest. Expected yield and yield volatility are estimated from the field experiment data. A range of coefficients of absolute risk aversion are used in the computations. The results suggest that yield volatility is large and it dominates the price volatility in the optimal hedging decisions of the Finnish wheat producers. The point estimate for the price and yield correlation is negative and has a large magnitude. Thus, a negative correlation between the price and the yield, as signalled by the point estimate, will decrease the optimal hedging ratio since the Finnish farmers do not have access to selling put options when they enter in a forward contract.

A comparative study of risk exposure in agriculture and aquaculture

“…Nevertheless, the magnitude of grain yield variability in our study is quite similar to results from farm-level studies in Kansas (Marra & Schurle, 1994) and Manitoba (Popp & Rudstrom, 2000) and experimental trials in Finland (Liu & Pietola, 2005). Rasmussen (1997) estimated a grain yield CV close to 0.20 for Danish farms while Webster and Williams (1988) reported a cereal yield CV around 0.10 for English farms.…”

“…Nevertheless, our results suggest that yields and prices tend to move in opposite directions at the producer level for most of the agricultural commodities examined (Table IV), as often reported in other studies (e.g. Harwood et al, 1999;Liu & Pietola, 2005). The negative price-yield correlations provide producers with an offsetting relationship (''natural hedge'') that makes their incomes less variable than otherwise.…”

“…Managers do however tend to associate risk with the negative outcomes, and a risky choice is one that contains the threat of a negative outcome that affects an individual's welfare (March & Shapira, 1987). Hardaker et al (2004) pointed out that the best route to risk efficiency is by finding strategies that improve the expected values of returns, rather than those that reduce dispersion.…”

Does crop rotation with legumes provide an efficient means to reduce nutrient loads and GHG emissions?

“…However, many papers have indicated the presence of risk-averse behavior (see for instance Saha et al 1994;Hennessy 1998;Koundouri et al 2009). For Finland, Liu and Pietola (2005) found that yield risk is the dominant risk for farmers. A study by Koundouri et al (2009) showed that for Finnish farmers, risk attitudes vary across farm size; the change from small to large farms (with the mean and medium size of 44 ha) representing a change from risk aversion to risk loving.…”

Productivity growth on Finnish grain farms from 1976 2006: a parametric approach

“…This is because most of the inputs are applied in the spring on the basis of expected yields, but the output is strongly affected by the weather conditions during the growing season. Liu and Pietola (2005) showed that yield volatility is large and dominates price volatility in Finnish wheat production. Nauges et al (2009) reported that between 1995 and 2003, the yield explained 80% of the variation in annual wheat revenues, while the price explained 18% and the acreage only 2%.…”