Farm-level Acreage Allocation under Risk

We model the area allocation decision problem for a fixed size crop farm under random yields and prices for a risk-averse farmer. We assume that in the short run, the variable input expenses are fixed per hectare and per crop (an assumption that is motivated by our data). Therefore the cost function depends only on the non-stochastic area allocation. The first order conditions of the model involve integrals across functions of random variables that do not in general have closed form solutions. Numerical simulation techniques are used to calibrate the parameters of the cost function. The two sources of randomness, price and yield, are combined into a single random variable, the yield-in-value. Based on examination of panels of yield-in-value data, we assume independence across the yield-in-value distributions and that the farmers know these distributions. We have modeled the sugar quota constraint, the Common Agricultural Policy subsidies and set-aside, and one Agri-Environmental Measure called "buffer zone".Risk and Uncertainty,

Multi-input Multi-output Farm-level Cost Function: A Comparison of Least Squares and Entropy Estimators

We introduce a modification of the quadratic-Leontieff multi-output cost function that is particularly suitable for the data of the Farm Accountancy Data Network. We present least squares and entropy estimates of that function and compare their results for a sample of crop farms. Our results are encouraging for the use of entropy estimators in cases in which farms are not assumed to share the same technology. Our approach can be seen as an extension of the Positive Mathematical Programming approach (Howitt, 1995). The extension consists in an explicit specification of inputs in the cost function and in the possibility of modeling several farms simultaneously.cost function, least squares estimator, entropy estimator, heterogeneity, Farm Management, C3, D61, Q12,

Estimating an Ex Ante Cost Function for Belgian Arable Crop Farms

We estimate a farm-level cost function for Belgian crop farms using FADN data over the study period 1996-2006. We rely on an estimation of farmers' expected yields at the time cropping decisions are made rather than actual yields observed in the FADN data. The use of an ex ante cost function improves the cost function estimation. We subsequently suggest how our cost function can be used in simulations to analyze farmer response to changes in output price risk.cost function estimation, panel data, risk, Agricultural and Food Policy, Crop Production/Industries, Production Economics, Q12, Q18,