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Argentina’s Soybean Acreage Response to Changes in Price Incentives

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  • Luis Lanteri

    ()
    (Central Bank of Argentina)

Abstract

Agriculture in Argentina encompasses the entire range of field crop and livestock activities, including corn, wheat, sunflower and soybeans. Most notably, Argentina is the world’s leading exporter of soybean products (soyoil and soymeal) and ranks thirds behind the United States and Brazil as a producer and exporter of soybeans. The soybean complex accounts for more than 25 percent of the total exports in our country. Argentina’s soybean sector did not emerge until the early 1970s lagging Brazil by more than a decade. In 1970, only 36.000 hectares of soybeans were harvested in Argentina, compared with 1.7 million hectares in Brazil and over 17 million in the United States. Once soybean production gained a foothold, a strong natural comparative advantage over cereal production continued to boost plantings in Argentina. By 1990, 5.0 million hectares were planted to soybeans and production reached nearly 10.8 million tons. This expansion involved both new land entering soybean production as well as a shift of existing farmland from coarse grains, pasture and others. Soybean production continued to increase rapidly in Argentina, growing at nearly 8 percent per year since 1990 and continuing to accelerate into the late 1990s and 2000s. In 2006, 16 million hectares of soybeans were harvested (production 47.5 million tons). However, unlike the substantial yield improvements of the previous years, soybean production growth in the last decades was almost entirely the result of continued area expansion. Initially, Argentina’s soybean area expanded mostly in the central production zone in the heart of the Pampas. The central provinces of Cordoba, Buenos Aires and Santa Fe dominate soybean production. However, in recent years, the soybean area in the northern and northwestern states has also expanded. The rapid expansion of soybean area in Argentina has received a boost from the adoption of biotech soybeans and from the availability of early maturing varieties that help to diminish weather risk. Improved weed control also benefited the subsequent rotational crop, while early maturing varieties improved the potential for double cropping in the same year (wheat-soybeans). In the 1960s and 1970s, econometric models of agricultural supply, either at the sector level or at commodity level, were formulated, in general, in terms of time series, following the model proposed by Nerlove (1958) and by Grilliches (1959) and referred as adaptative expectations and partial adjustment models, respectively. In particular, Nerlove’s model requires a one-step direct estimation of production as a function of prices and other relevant variables. These models suffered problems of spurious regressions frequently. This paper deals with the question of how responsive farmers in Argentina are to changes in incentives. We employ Johansen’s (1988) and Johansen and Juselius (1990) multivariate cointegration approach and covering the period 1974-2006. The paper investigates for this country the long-run effect of pricing policies, risk and certain non-price factors on soybean acreage. The models are estimated from variables measured in levels and should the suspicion of non-stacionarity be confirmed by the data. In those cases where cointegration relationships are found, estimated supply elasticities tend to lay between 2.37 and 5.24 by the total country. The model includes the area planted to soybeans as a function of expected relative prices (in terms of the best technical alternative), the use of some inputs, risks and other variables relevant in the agricultural production. The results show an important response of soybean supply with respect to economic incentives. In terms of policy these supply elasticities mean that depressed prices may cut down substantially soybean production from one year to the next, or on the other hand, a spectacular increase in area planted could be expected from an increase in the level of soybean relative prices.

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Bibliographic Info

Article provided by Central Bank of Argentina, Economic Research Department in its journal Ensayos Económicos.

Volume (Year): 1 (2008)
Issue (Month): 52 (October - December)
Pages: 57-86

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Handle: RePEc:bcr:ensayo:v:1:y:2008:i:52:p:57-86

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Related research

Keywords: agricultural products; Argentina; elasticities; relative prices; risks; soybean supply;

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References

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  1. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  2. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
  3. Schiff, Maurice & Montenegro, Claudio E., 1995. "Aggregate agricultural supply response in developing countries : a survey of selected issues," Policy Research Working Paper Series 1485, The World Bank.
  4. Diego Bastourre & Jorge Carrera & Javier Ibarlucia, 2008. "Commodity Prices in Argentina: What Moves the Wind?," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(51), pages 43-81, April - S.
  5. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
  6. Hallam, David & Zanoli, Raffaele, 1993. "Error Correction Models and Agricultural Supply Response," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 20(2), pages 151-66.
  7. Mamingi, Nlandu, 1997. "The impact of prices and macroeconomic policies on agricultural supply: a synthesis of available results," Agricultural Economics, Blackwell, vol. 16(1), pages 17-34, March.
  8. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
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