|Home > Estimating a production function under production and price risks: An application to the suckler cow farms in the French charolais production area|
Suckler cow production in France relies mainly on a relatively extensive management of forage, implying that production risk may be enhanced by the sensitivity of those crops to weather variability. However risk exposure is supposed to be mitigated either through ex-ante decisions concerning pasture area management or through ex-post decisions concerning the purchase of feeds. This paper aims at assessing weather impacts on cattle production level decisions. Since farmers' decisions depend on farmers' behaviour regarding risks, which are namely production and price risks, we test constant absolute risk aversion, constant relative risk aversion and risk neutrality assumptions. We develop an econometric model encompassing an auto-regressive price function and a production function which allow inputs to affect independently mean and variance of the production. Weather indicators embodied by average regional forage production for current and past years are explicitely introduced as non controllable inputs. The estimation framework consist in conditions on the first and second moment of output production, output price and profit. Following, ISIK (2003), additional condition on each of both allocable inputs enable us to take into account risk aversion and both price and production risks in parameters estimation. We use the Generalized Method of Moments in order to make minimum assumptions regarding variable exogeneity and error distribution. We apply the model to an original panel dataset containing 65 individual yearly observations recorded over the period 1987-2005 on French suckler cow farms of the north of Massif Central. Because of the difficulties to find a relevant set of instruments, these preliminary results do not analyse weather impact on production mean. However we can advance that production decisions depend on price and production risks as farmers are found to be risk averse. Weather variability of the current year increase production risk whereas fertilizer level application slightly increased it. However we did not highlight that weather impact depend on production level.