This dissertation examines measurement problems caused by imperfect data and productivity issues in a microeconometric framework. The empirical work is done on a panel of 384 farmers in the Zona da Mata region of Minas Gerais, Brazil, for the period extending from 1979-84. The farmers use modern, labor and traditional inputs towards the production of two broad categories of outputs: crops and livestock. The first goal is to study estimation methods of agricultural input demand systems in the light of imperfect data and compare the consequences of not taking data quality into account versus when they are. These problems are addressed using techniques that include discrete choice models and virtual price methods. The second goal is to measure and examine the productivity of farmers and investigate the sources for existing variations in efficiencies. This is done using Stochastic Frontier Analysis methods and Data Envelopment Analysis. Besides the estimation of efficiency scores, investigating the effects of tenancy status and input-use on productivity are also addressed. The final goal is to link the above treatments empirically. This is done by examining the degree of misspecification that might arise from a failure to include the efficiency measures in the estimation of demand systems
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