Economic Analysis of the Agricultural Sector in Santa Cruz, Bolivia

Open Access

Abstract

A linear programming technique is used to calculate the land allocation that maximizes the returns to the agricultural producers in the provinces Santisteban, Sara, Warnes, Ibanez, and Ichilo, in the department of Santa Cruz, Bolivia, under different sets of prices. All the input requirements per unit of land and average expected yields are estimated from survey data collected from farmers in Bolivia. Constraints on availability of land and labor are also estimated. Seven crops are included in the model: soybeans, wheat, cotton, yuca, sugar cane, rice, and corn. The model is first examined under the set of prices that existed prior to the 67 percent devaluation of the Bolivian currency of October 1972. Supply schedules are calculated for each one of the crops. Later, the price changes caused by the devaluation are introduced into the model, and their impact upon the "optimum" land allocation in the area is ascertained. A supply curve is derived for cotton under "after devaluation" prices. The effect of an export tax, on land utilized for cotton production is analyzed. It is estimated that a 40 percent tax on cotton production, other things being equal, would render cotton production unprofitabl e . A 23 percent tax would maximize the Government tax revenues. The net social cost of implementing such a tax is estimated at $b 101.6 millions per year. A self-sufficiency national policy is examined for wheat production. If the Government desires self-sufficiency in wheat production while maintaining the real price to the consumers at the pre-devaluation level, (that is, $b 46.75 per cwt before devaluation, and $b 70.12 per cwt after) the producers would have to be paid $b 150.0 per cwt, the difference between the pegged consumer price and the price paid to producers being covered by a Government subsidy. The total cost to the Government for the subsidy is estimated at $b 642.7 millions per year, and the net social loss is $b 141.2 millions per year.