TECHNOLOGICAL CHANGE AND THE PRODUCTIVITY SLOWDOWN IN FIELD CROPS: UNITED STATES, 1939-78

In the past four decades, productivity in United States field crops has been transformed by the mechanical and fertilizer revolutions. Since input data are typically not available by crop, most investigators of productivity have been at the aggregate level. This paper developps a simultaneous equation, partial adjustment model of the demand of inputs, which generates estimates of the technical change parameters for wheat, corn, soybeans, and cotton. These estimates allow comparisons of the factor saving biases in technical change, leading to a novel test of the induced innovation hypothesis and the suggestion that the productivity slowdown may yet affect agriculture in the United States.Research and Development/Tech Change/Emerging Technologies,

CAN GM-TECHNOLOGIES HELP AFRICAN SMALLHOLDERS? THE IMPACT OF BT COTTON IN THE MAKHATHINI FLATS OF KWAZULU-NATAL

Analysis of a survey of the 1998-99 and 1999-2000 seasons for the same 100 smallholders in the Makhathini Flats region of KwaZulu-Natal shows that Bt cotton has performed better than other varieties. Having two years of data for the same farmers allows innate efficiency differences, due to factors such as farm size, to be separated from the effects of the new technology, which is not normally possible. Farmers who adopted Bt cotton in 1999-2000 benefited according to all the measures used. Higher yields and lower chemical costs outweighed higher seed costs, giving higher gross margins. These measures showed negative benefits in 1998-99, which conflicts with continued adoption, but stochastic efficiency frontier estimation, which takes account of the labor saved, showed that adopters averaged 88% efficiency, as compared with 66% for the non-adopters. In 1999/2000, when late rains lowered yields, the gap widened to 74% for adopters and 48% for non-adopters.KwaZulu-Natal, Bt cotton, Stochastic Frontiers, Efficiency, Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

Technical innovation and farm productivity growth in dryland Africa: The effects of structural adjustment on smallholders in Kenya

This paper uses non-parametric approach to measure technical innovation and productivity growth at the smallholder farm-level in dry-land sub-Saharan Africa during the initial years of the structural adjustment programmes for agriculture. Data from Kenya for two production years, 1991/2 and 1995/6 are used to construct a Malmquist productivity index. The results show that the rise in input prices led to reduced use of modern inputs, so that efficiency increased at 12% per year. However, lower use of modern varieties and less fertiliser also gave technological regression at 2.5% per annum, so that the overall outcome was productivity growth of 3% per annum. However, productivity improvement cannot be sustainable without technological progress.Farm Management, Productivity Analysis, Research and Development/Tech Change/Emerging Technologies,

THE RELATIONSHIP BETWEEN FARM SIZE AND THE TECHNICAL INEFFICIENCY OF PRODUCTION OF WHEAT FARMERS IN THE EASTERN FREE STATE

Some comments are required to put in perspective the results obtained by Ngwenya, Battese and Fleming (1997). In particular, it is necessary to examine their main conclusion that in 1988/89 there was a significant inverse relationship between the technical inefficiency of wheat farmers in the Eastern Free State and farm size, because this is in direct contrast with the findings of Van Zyl, Binswanger and Thirtle (1995) who used the same dataset.Crop Production/Industries,

Production Incentives for Small Scale Farmers in Zimbabwe: The Case of Cotton and Maize

The paper presents an empirical investigation of the production response of small scale producers of maize and cotton for communal agriculture in Zimbabwe. The error correction model, which employs the concept of cointegration to avoid spurious regressions, is used in the analysis. The factors affecting maize output were the price of maize relative to seed, the number of marketing depots established in the communal areas and the number of loans provided to these farmers. The factors affecting cotton output were the increase in communal lands due to the resettlement program, the number of loans extended to small scale farmers and the price of cotton relative to seed. The weather played the most significant role in determining the quantity of maize sold.Agricultural and Food Policy, Crop Production/Industries,

THE IMPACT OF RESEARCH LED AGRICULTURAL PRODUCTIVITY GROWTH ON POVERTY REDUCTION IN AFRICA, ASIA AND LATIN AMERICA

Twenty percent of the world population, or 1.2 billion live on less than $1 per day; 70$144 and in Asia $180, or 50 cents per day, but this is covered by output growth. By contrast, the per capita cost for the richer countries of Latin America is over$11,000.Agricultural Productivity, Poverty Reduction, Food Security and Poverty, Research and Development/Tech Change/Emerging Technologies, 011, 013, 015,

Efficiency and Pooling in Western Cape Wine Grape Production

This paper uses a stochastic frontier and inefficiency model to test the efficiency of grape production in the Western Cape. The data covers two panels of wine grape farms (34 in Robertson and 36 in Worcester) for 2003 and 2004 and 37 table grape farms in De Doorns for 2004 only. Tests show that Cobb Douglas stochastic production frontiers, with variables to explain the inefficiencies are an appropriate representation of the five individual samples. The stochastic frontier results indicate that output can be explained by land, labour and machinery and that efficiency cab be affected by labour quality, age and education of the farmer, location, the percentage of non-bearing vines and expenditures on electricity for irrigation. These data is sufficiently good to produce reasonable results without pooling, but most applied economists would consider the possibility of improving the estimates by pooling the samples. However, pooling tests show that in this situation with small samples, when pooling is permissible it may not be helpful. More effort on determining the true distributions is needed to improve the way such samples are handled and Bayesian methods may be helpful in this respect.Crop Production/Industries, O13, Q12,

Agricultural technology, productivity and employment: Policies for poverty reduction

This paper begins by arguing that agricultural economics has an important contribution to make to the economic transition of the new democratic South Africa. Policies are required to reduce unemployment, poverty and inequality, but does the work of agricultural economists provide the policy makers with the information necessary to make the correct choices? In this context, we update our recent work on technology, efficiency and productivity in South African agriculture, for both the commercial and smallholder sub-sectors. For the commercial sector, this means extending the total factor productivity index and estimates of the demand for labour. For the smallholder sector, there are new results on the impacts of GM cotton and white maize on output and employment. However, this piecemeal approach treats the two sectors as entirely separate, when they are actually interdependent. Thus, a Ricardian model of dualistic agriculture is used to explain the historical development of dualism in agriculture, especially how the native agriculturalists were impoverished by the colonists. Then this model is adapted to resemble the Harris-Todaro model of urban unemployment is order to represent the present dual agricultural sector. This allows the current policy options to be compared, although real data is needed to estimate the relationships and so the full analysis remains incomplete.Agricultural and Food Policy, Food Security and Poverty,

Testing the induced innovation hypothesis in South African agriculture (an error correction approach)

The authors investigate whether factor prices matter in agricultural production and in the selection of production technology. Each stage of the analysis corroborates the inducement hypothesis, which implies that factor prices do matter in agricultural production and in the selection of production technology. The empirical results also suggest that observed rates and biases of technological change are influenced by average farm size, by spending on research and extension, and by favorable tax and interest-rate policies. In South Africa, the authors contend, more attention should be focused on the technological needs of small-scale farmers. The lobbying power of the large commercial farmers, combined with policies followed under apartheid, must have influenced the allocation of research and development funds between labor- and land-saving technical change. This will have distorted the technological bias toward labor saving technical change, which is hardly appropriate for a labor-surplus economy in which small farmers in the former homelands face a chronic scarcity of land. These results show that factor prices do matter in agricultural production and the selection of production technology. And there seems to be merit to the World Bank's usual policy prescription - structural adjustment and market liberalization - for economies in which prices are controlled and distorted. They investigate the role of factor prices by applying cointegration techniques to a model of induced innovation based on the two-stage constant elasticity of substitution production function. This approach results in direct tests of the inducement hypothesis, which are applied to data for South African agriculture for the period 1947-92. They check the time series properties of the variables, establish cointegration, and construct an error correction model (ECM) that allows factor substitution to be separated from technological change. Finally, they subject the ECM formulation to tests of causality, which show that the factor price ratios induce the factor saving biases of technological change.Economic Theory&Research,Environmental Economics&Policies,Agricultural Knowledge&Information Systems,Scientific Research&Science Parks,Markets and Market Access,Environmental Economics&Policies,Economic Theory&Research,Agricultural Knowledge&Information Systems,Scientific Research&Science Parks,Science Education

Prospects for agricultural productivity growth : will there be a slowdown in developing countries?

The food price spikes of 2008 showed that world food security is not a foregone conclusion. With this in mind, we distinguish between three productivity measures, as their implications differ. These are: yields, which, with area harvested, determine output; labour productivity, which correlates with incomes; and total factor productivity, which distinguishes between technical progress, efficiency change and input intensification. Hence TFP growth has different implications, according to its cause. The World Development Report (World Bank, 2008) distinguishes between the agriculture-based, transforming, and urbanised countries that constitute agriculture’s three worlds. The first is dominated by Sub-Saharan Africa (SSA), with much of Asia and the Middle East and North Africa (MENA) region in the transitional group, while and urbanised developing economies are mostly in Eastern and Central Europe and Latin America. We would add the developed countries (DCs) that are loosely member states of the OECD. The DCs are not the focus, but the slowing of public agricultural R&D growth in this group, plus low rates of GDP growth and possibly agricultural productivity measures, have connotations for all the others, as these countries are the initial source of scientific advances and technologies. We find a tendency for yield and labour productivity growth to slow from the mid 1980s, but TFP did not slow down in all countries. What did happen more generally, is that TFP growth was maintained by input reduction, rather than output growth, as investment in agriculture declined due to lack of profitability. This is why the supply response in 2008 was rapid, but as it was achieved by increasing modern inputs, TFP will have been reduced, although yields should have risen. There is some consensus that new technology is not being generated as it once was, but here there is a gulf between North America, where private sector GM varieties have filled the gap and Europe where they have been largely excluded. If there is less technology internationally available from the world’s leading national agricultural research stations (NARS), the effect on the urbanised countries may not be great. The Eastern and Central European countries have to long way to go to increase efficiency levels to match Northern Europe, so reorganisation matters more than technical progress. In Latin America, countries like Brazil and Argentina are industrialising and commercialising agriculture and have their own research capacity that may well increase yields as a result. They are almost certain to increase labour productivity as agriculture is mechanised and TFP should be driven by labour productivity growth. For the upper end of the transforming countries the same is true, as China and India have the research capacity to generate yield growth and the withdrawal of labour from agriculture will raise labour productivity and TFP. It is the smaller countries, with less research capacity and less industrialisation that may be at risk from productivity stagnation if they do not attract private technology providers. The agriculture-based countries range from the small failed states of SSA to countries like Kenya, which has quite reasonable research capacity. All the TFP studies show that SSA lags behind, but that productivity has been improving since the mid 1980s. The key seems to be institutions, incentives and better policy and infrastructure. It is efficiency change, rather than new technology and SSA could have reasonable growth in TFP and yields on this basis alone. A major difference between Asia and Africa is that in Asia, yield growth has been translated into increased labour productivity and better incomes. In SSA, yield increases have improved labour productivity very little, so there is a difficult question as to whether the relatively land abundant countries can follow a path of labour saving technical change. The unknowns that will determine the future course of agricultural development centre around energy and climate change. With the oil price at below $40 per barrel, the biofuels industry is not currently a problem, but once the recession is over the issue of food versus fuel will reappear. Agriculture will need to adjust to more expensive fertiliser, fuel and transport, while pushing towards sustainability and lower environmental costs. It remains to be seen how energy efficient technologies can be developed with lower public R&D growth and with many countries still avoiding any science that includes GM