Projecting China’s Grains and Meats Trade: Sensitivity to agricultural productivity growth

Literature from the past 20 years is reviewed to establish the range of TFP growth estimates that have been made for China’s agriculture. This includes some studies that have focussed on either the crops or livestock subsectors. The dispersion of these estimates is used as an input to a slightly-modified GTAP model in order to determine the sensitivity of China’s projected grains and meats trade balances to agricultural productivity growth. For many variables, results indicate a high degree of sensitivity, and a number of ways are suggested by which such projections might be enhanced through improved productivity measurement. * Presented at International Agricultural Trade Research Consortium Annual General Meeting, session on Research Plan and Reports, San Antonio, Texas, 14-16 December 2003. Financial support from the Massey University Academy of Business Research Fund and FRST contract number IERX0301 is gratefully acknowledged. Introduction China’s agricultural output has expanded rapidly since the economic reforms of the late 1970s, reflecting both productivity growth and mobilisation of inputs. Over the 1980-2000 period wheat output has doubled and that of maize has risen by about 70%. Among livestock products, output of poultry has increased tenfold, egg output has increased sixfold and that of pork by three times. Over the same period China’s rapid economic growth and urbanisation have pushed consumption patterns towards increased consumption of high-value foodstuffs including livestock products. Will China’s food output expansion be able to match consumption growth in the future? Urban and rural industrialisation is drawing labour, capital and land away from agricultural employment, and growing environmental awareness could increase pressures to moderate the use of fertilisers and pesticides. Further, the current land tenure system hinders the achievement of scale economies and constrains the expansion of labour-saving agricultural technologies. The above question, along with China’s heightened involvement in global food markets as both an importer and exporter, has spurred debate over whether or not China will be able to feed itself, and if not what might be the consequences for global markets? Perhaps the most (in)famous and pessimistic projection was that of Brown while others (e.g. Fan and Agcaoili-Sombilla) have shed considerable doubt on his scenario of soaring prices and widespread starvation. Nevertheless, several studies have since projected emerging grain deficits in response to population and income growth, urbanisation, a shift in comparative advantage from land-intensive to labour-intensive commodities, and increased demands for livestock feedstuffs. Turning to meats, China has been a net exporter (in value terms) of pigmeat and poultry, a net importer of beef, and overall a net exporter of fresh and prepared meats. Is this likely to continue? Rosegrant et al. projected meat imports rising from near trade balance in 1997 to a 4 million tonne deficit by 2020. Delgado et al. projected a decline in pork net exports but an increase in the case of poultry by 2020. In contrast, both Rutherford and Huang et al. (2000) projected continuing Chinese self-sufficiency in meats. Given possible policy and resource constraints, achievement of the Chinese government’s goal of food self-sufficiency would appear to have to rely on continuing improvements in agricultural productivity. It follows that the measurement of agricultural productivity will become crucial for estimating the future supply of domestic agricultural commodities and in turn for predictions of future grain and meat trade balances. However, the estimation of China’s past productivity growth, let alone the formulation of future projections, has also been controversial. The following section reviews past studies, and it will be apparent that the range of measured productivity growth rates is wide. While this reflects in part the variety of estimation techniques and differences in the definition of outputs and inputs, considerable doubt has been cast on the reliability of the underlying agricultural statistics. Only recently have some researchers made efforts to adjust for discrepancies in existing data series or to access alternative data sources. The paper then makes use of a CGE model to