IMPLICATIONS OF AGGREGATION BIAS FOR THE CONSTRUCTION OF STATIC AND DYNAMIC LINEAR PROGRAMMING SUPPLY MODELS*

Abstract
Aggregation bias is acknowledged to be one of the more serious problems confronting the Linear Programming approach to supply analysis. Whilst the literature abounds with theoretical solutions to the problem there is a notable lack of ideas on how these solutions might be made operational. This conclusion holds a fortiori for the dynamic case. This paper discusses a practical methodology for the classification of farms in order to minimise aggregation bias, and also the implications of avoiding bias for the specification of dynamic linear models.

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