Flexible quota constraints in positive mathematical programming models

To explain over- and underuse of available quota, Buysse et al. (2007) have integrated the shadow cost of the quota constraint in a quota flexibility function in a positive mathematical programming model. This method and central hypothesis, formulated and tested for the case of Belgian sugar beet farms, is in current paper extended and confirmed for the cases of Flemish dairy quota and manure emission rights. Despite the different organisation, objectives and implementations of the diverse quota systems, the results are similar. A higher utilisation of quota is significantly driven by the quota rent, but farm characteristics are also important and the effect declines with increasing quota rent. Regardless the quota, the dairy quota flexibility behaviour of the sample of Flemish farms results in an output price elasticity of 0.6%. The quota flexibility functions can be used for policy analysis, model sophistication and farm advisory instrument.Quota, flexibility, Positive Mathematical Programming, farm model, Common Agricultural Policy, Agricultural and Food Policy, Demand and Price Analysis, Research Methods/ Statistical Methods,

Simple econometric models for short term production choices in cropping systems

The aim of this article is to present new models of acreage choices to describe short term production choices. Its construction combines concepts developed in the Positive Mathematical Programming and Multicrop Econometric literatures. They consider land as an allocable fixed input and motivate crop diversification by decreasing returns to crop area and/or implicit costs generated by constraints on acreage choices and by limiting quantities of quasi-fixed factors. Attractive re-parametrization of the standard quadratic production function and different functional forms for cost function are proposed to have parameters easily interpretable and to define econometric models in a very simple way.Acreage share; Production function; Multicrop econometric model; Positive Mathematical Programming

Application of semidefinite programming to maximize the spectral gap produced by node removal

The smallest positive eigenvalue of the Laplacian of a network is called the spectral gap and characterizes various dynamics on networks. We propose mathematical programming methods to maximize the spectral gap of a given network by removing a fixed number of nodes. We formulate relaxed versions of the original problem using semidefinite programming and apply them to example networks.Comment: 1 figure. Short paper presented in CompleNet, Berlin, March 13-15 (2013

Evaluating Changes in Cropping Patterns due to the 2003 CAP Reform. An Ex-post Analysis of Different PMP Approaches Considering New Activities

Replaced with revised version of paper 02/22/08.ex-post policy evaluation, positive mathematical programming, CAP reform, Agricultural and Food Policy, Crop Production/Industries, Research Methods/ Statistical Methods,

STRATEGIC AGRIBUSINESS OPERATION REALIGNMENT IN THE TEXAS PRISON SYSTEM

Mathematical programming-based systems analysis is used to examine the consequences of alternative operation configuration for the agricultural operations within the Texas Department of Criminal Justice. Continuation versus elimination of the total operation as well as individual operating departments are considered. Methodology includes a firm systems operation model combined with capital budgeting and an integer programming based investment model. Results indicate the resources realize a positive return as a whole, but some enterprises are not using resources profitably. The integer investment model is found to be superior for investigating whether to continue multiple interrelated enterprises.agribusiness, enterprise selection, mathematical programming, optimal enterprise organization, Agribusiness,

Using the Positive Mathematical Programming Method to Calibrate Linear Programming Models

In agricultural economics, several calibration and aggregation approaches have evolved in mathematical programming models. This article combines in a linear programming model features of the Positive Mathematical Programming method with an aggregation approach that is constrained to the production possibility set spanned by a convex combination of observed production activities. The combination is obtained by using a variable separation technique that approximates a non-linear objective function. Therefore, linear programming models can be exactly calibrated to observed production activities. The aggregation of production activities in homogenous production response units assumes that farmers in a region are treated such as they respond in the same way. Both methodologies are embedded in economic reasoning and provide a robust framework to solve large-scale linear programming models in reasonable time

A Fully Calibrated Generalized CES Programming Model of Agricultural Supply

The use of prior information on supply elasticities to calibrate programming models of agricultural supply has been advocated repeatedly in the recent literature (Heckelei and Britz 2005). Yet, Mérel and Bucaram (2009) have shown that the dual goal of calibrating such models to a reference allocation while replicating an exogenous set of supply elasticities is not always feasible. This article lays out the methodological foundation to exactly calibrate programming models of agricultural supply using generalized CES production functions. We formally derive the necessary and sufficient conditions under which such models can be calibrated to replicate the reference allocation while displaying crop-specific supply responses that are consistent with prior information. When it exists, the solution to the exact calibration problem is unique. From a microeconomic perspective, the generalized CES model is preferable to quadratic models that have been used extensively in policy analysis since the publication of Howitt’s (1995) Positive Mathematical Programming. The two types of specifications are also compared on the basis of their flexibility towards calibration, and it is shown that, provided myopic calibration is feasible, the generalized CES model can calibrate larger sets of supply elasticities than its quadratic counterpart. Our calibration criterion has relevance both for calibrated positive mathematical programming models and for “well-posed” models estimated through generalized maximum entropy following Heckelei and Wolff (2003), where it is deemed appropriate to include prior information regarding the value of own-price supply elasticities.Positive mathematical programming, generalized CES, supply elasticities, Crop Production/Industries, Production Economics,

Positive Mathematical Programming: a Comparison of Different Specification Rules

In this paper, the prescriptive capacity of different types of positive mathematical programming models applied to the Alentejo agricultural sector is analysed. Model results are compared for 2000 and 2004 agricultural price and subsidies scenarios, regarding optimal combination of activities. Thus, it is tested, on one hand, models capacity to reproduce Alentejo agricultural sector behaviour, and by the other hand, their response and adjustment capacities to changes in prices and in agricultural policy.Positive mathematical programming, agricultural supply, Alentejo, Research Methods/ Statistical Methods,

UTILIZATION OF RELATIVE LAND ALLOCATION IN THE CALIBRATION OF AGRICULTURE SUPPLY MODELS BY THE PMP APPROACH

This poster proposes a new procedure in agriculture supply modelling by the positive mathematical programming (PMP) approach. This approach is now widely used in last CAP reform simulations. However, simulation behaviour and performances of PMP procedures depend of the way parameters of the non linear total cost function in the objective function are recovered. We propose a new specification of the total cost function where land is explicitly considered as a fixed input. By using relative parts of land of the different activities this new PMP procedure permits to better capture production behaviour when economic conditions. It also permits to avoid a drawback of the early procedures concerning marginal activitiesPositive Mathematical Programming, CAP, Agricultural and Food Policy, Research Methods/ Statistical Methods, Q10, Q18,