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    <abstract>This report presents empirical estimations of Indian farmer&apos;s land allocation decisions. Farmers&apos; decisions about what crops to grow and on how much land are modeled to be rational and consistent with utility maximization in the context of opportunities and expectations about future rain fall, yields, and prices. 

The authors find application of the conventional adaptive expectation Nerlovian model to Indian data to be inappropriate; specification of the price expectation in this model is inadequate because it implies that farmers do not distinguish between trends and occasional random shocks.  This report differs from the conventional approach in 

1. Using expected revenue instead of expected prices as a proxy for expected profits. 

2. Using auto-regressive integrated moving average (ARIMA) model to model crop revenue expectations. 

The revenue expectation functions, estimated separately, are used to compute revenues relative to those of major competing crops, which are identified on the basis of sowing and harvesting periods. The estimated acreage response equations are also tested in a validation exercise for 16 major Indian crops.</abstract>
    <date>1981-02</date>
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