A multiperiod linear programming model of farm growth and bmp adoption in southeastern Virginia

Firm growth and best management practice (BMP) adoption of a representative, diversified, southeastern Virginia, farrow to finishing hog farm is examined in a multi-period linear programming framework. Specific attention is focused on the acquisition of additional productive resources and the impact...

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Bibliographic Details
Main Author: Faulkner, David Linzey
Other Authors: Agricultural Economics
Format: Others
Language:en
Published: Virginia Polytechnic Institute and State University 2020
Subjects:
Online Access:http://hdl.handle.net/10919/101431
Description
Summary:Firm growth and best management practice (BMP) adoption of a representative, diversified, southeastern Virginia, farrow to finishing hog farm is examined in a multi-period linear programming framework. Specific attention is focused on the acquisition of additional productive resources and the impact of BMP adoption on the optimal combinations of crop and livestock activities over a five year planning horizon. The maximization of after-tax net income was employed as the objective function of the model. Increases in terminal net worth were transferred to the objective function at the end of the planning period. Two sets of model solutions were obtained; one set with cost-share subsidies and the other without. Results indicate that farm growth potential exists with or without cost-share subsidies and that the current high costs of external capital tend farmers toward use of internal financing. The availability of labor during peak periods ultimately constrained the growth process. The specific direction of the modeled farm's growth led to the investment in a totally confined slatted-floor house means of hog production. The model demonstrated a decic;!ed preference for the use of investment tax credits over the direct expense deduction provision of the federal income tax code. In general, sod filter strips, grassed waterways and no-till cropping proved to be the most cost-effective BMPs in achieving nonpoint source pollution objectives. === M.S.