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Este trabajo analiza la eficiencia unificada bajo tres enfoques natural disposability, managerial disposability, y bajo los dos anteriores juntos natural y managerial disposability. Además analiza los tipos de Rendimientos a Escala (RTS) y los Daños a Escala (DTS), en el sector agrícola de América Latina y El Caribe (ALC) durante el año 2012. Las diferentes medidas se estiman utilizando la técnica matemática no paramétrica Análisis de Envolvente de Datos (DEA), para la evaluación medioambiental, que permite descomponer el desempeño agrícola en medidas de eficiencia. Para ello, se utilizan las ocho variables convencionales de la agricultura: la alimentación animal, consumo de fertilizantes, reserva de capital-cultivo, reserva de capital-ganado, población económicamente activa, la tierra agrícola, valor de la producción agrícola y emisiones agrícolas. Los resultados obtenidos indican una mayor eficiencia bajo natural disposability en los países evaluados. Bajo este enfoque, la mayoría de los países presentan RTS constantes y RTS decrecientes, mientras bajo managerial disposability tienden a DTS constantes y DTS crecientes Ministerio de Economia y Competitividad TIN2013-46801-C4-1-r Ministerio de Economia y Competitividad P11-TIC-8052 Junta de Andalucía P11-TIC-7124 Junta de Andalucía SEJ-132

This study estimates Climate Adjusted Total Factor Productivity (CATFP) for agriculture in Latin America and Caribbean (LAC) countries, while also providing comparisons with several regions of the world. Climatic variability is introduced in Stochastic Production Frontier (SPF) models by including average annual maximum temperature, precipitation and its monthly intra-year standard deviations, and the number of rainy days. Climatic conditions have a negative impact on production becoming stronger at the end of the 2000s compared to earlier periods. An Error Correction Model is applied to investigate catch-up and convergence across LAC countries. Argentina defines the frontier in LAC and TFP convergence is found across all South American countries, Costa Rica, Mexico, Barbados and The Bahamas. Using IPCC 2014 scenarios, the study shows that climatic variability induces significant reductions in productivity (2.3% to 10.7%), over the 2013-2040 period. Estimated output losses due to climatic variability range from 9% to 20% in the LAC region depending on the scenario considered.

This study estimates Climate Adjusted Total Factor Productivity (CATFP) for agriculture in Latin America and Caribbean (LAC) countries, while also providing comparisons with several regions of the world. Climatic variability is introduced in Stochastic Production Frontier (SPF) models by including average annual maximum temperature, precipitation and its monthly intra-year standard deviations, and the number of rainy days. Climatic conditions have a negative impact on production becoming stronger at the end of the 2000s compared to earlier periods. An Error Correction Model is applied to investigate catch-up and convergence across LAC countries. Argentina defines the frontier in LAC and TFP convergence is found across all South American countries, Costa Rica, Mexico, Barbados and The Bahamas. Using IPCC 2014 scenarios, the study shows that climatic variability induces significant reductions in productivity (2.3% to 10.7%), over the 2013-2040 period. Estimated output losses due to climatic variability range from 9% to 20% in the LAC region depending on the scenario considered.

This study analyzes the performance of Latin America and the Caribbean's agriculture between 1980 and 2012 looking at the contribution of inputs, and total factor productivity (TFP) to growth in output per worker. A growth accounting approach that goes along the lines of neoclassical growth accounting combined with Data Envelopment Analysis, allows us to measure TFP growth using output and input indices and also to decompose this growth into contributions of technical change and changes in technical efficiency. Our findings show that between 1980 and 2012, regional agricultural output per worker and TFP increased 82 and 45 percent, respectively, reducing the difference between TFP in LAC and in OECD countries. This improved performance of agriculture was the result of fast growth in the use of fertilizer, increases in land productivity, and growth in the use of capital that expanded cultivated area per worker. Higher productivity of the animal stock, fast growth in the use of feed and in the number of animals per worker, have increased the share of livestock in total output and also contributed significantly to the improved performance of agriculture. Observed growth patterns at the country level suggest that countries that increased input per worker have increased TFP at a higher rate than countries with limited access to capital and land. As a result of these growth patterns, the improved performance in the region has amplified differences in labor productivity between countries. Growing differences in labor productivity and the fact that the favorable shock in commodity prices that benefited LAC's agriculture in recent years has apparently ran its course, raise concerns for the future.

This paper analyses the impacts of climate change of food processing sectors worldwide. Specifically, we analyze the impacts that changes in agricultural productivity might have for seven food industry sectors, namely meat, vegetable oils and fats, dairy, sugar, processed rice, other food products and beverage and tobacco products. We analyze two different scenarios of crops yield changes based on Müller et al. (2009), one with full CO2 fertilization and one without CO2 fertilization. We use a general equilibrium approach, given the advantages that this methodology provides for worldwide analysis of productivity and its impacts on production, trade and prices of primary agriculture, and ultimately, food processing sectors. We use the GTAP computable general model with version 7 of the GTAP database, with a base year of 2004. We aggregate this database into 10 regions and 12 sectors, with special emphasis on food processing sectors. The results show that overall, the impacts on food processing depends whether we consider CO2 fertilization or not.

This paper analyses total factor productivity growth in agriculture and its subsectors in Latin America and the Caribbean between 1961 and 2007. To estimate productivity growth we use the Malmquist index, which is a non-parametric methodology that uses data envelopment analysis (DEA) methods. The results show that among developing regions, Latin America and the Caribbean shows the highest agricultural productivity growth, growing at an average rate of 1.9 percent, relative to a world average of 1.7 percent. The higher growth within the region has occurred in the last two decades, especially due to improvements in efficiency and the introduction of new technologies. This result denotes convergence of the region to productivity levels of developed countries such as the United States. Country level results within the region are very heterogeneous. However, land abundant countries such as Argentina, Chile and Colombia consistently outperform land constrained countries such as Central American and Caribbean countries (except for Costa Rica). Within agriculture, crops and non-ruminant sectors have shown the strongest growth between 1961 an 2001 with average growth rates of 0.8 and 2 percent, respectively. Ruminant production has performed the worst with 0.1 percent average growth. We further analyze the cases of Brazil and Cuba to show how policies and external shocks can influence agricultural productivity. These case studies show that policies that do not discriminate the agricultural sectors and that remove price and production distortions may help improve productivity growth in agriculture.

As the use of global and national computable general equilibrium (CGE) models has become more widespread, most policies still remain at the regional or sub-national level. This level of disparity requires an approach that bridges the gap between national results and sub-national policies. This study provides a methodology that combines micro-level information and the results of a CGE model with geographical information to spatially map the effects of trade liberalization on the agricultural sector. This methodology enables to distribute changes in value of production for each production unit according to the importance of a specific crop in the political administrative unit. These results show the geographic effects of the FTA on Ecuador's agriculture, and how various types of producers would be affected from trade liberalization. This kind of results would enable policy makers to formulate policies in a geographic or territorial way. This would also allow policy makers to implement differentiated policies to help different types of farmers groups cope with potential negative impacts from free trade.

Rising oil prices has led to increased interest to replace domestic demand for liquid fuels for transport (petrol and diesel) with biofuel production (ethanol and biodiesel). One of the pioneers in biofuel production is Brazil, which since the 1970s has established a government program that promotes the production and consumption of ethanol. Currently, Brazil is the leading producer of ethanol in the world and has started also programs for biodiesel production based on soybeans, oil palm and other crops. Other countries in Latin America and the Caribbean have also expressed interest in biofuel production, and have started programs, and in some cases the legislation that promotes biofuel production. However, most of the analysis of biofuel crops has been focused in the major countries such as Brazil and Argentina. As most countries in the region embark in biofuel projects and establish national policies on biofuels, there is a need for a roadmap that looks into the technical considerations that biofuel production will require. Most government policies are driven by politics, and in some cases such as the discussion of food production versus biofuel production, there should be technical analysis of increased production of biofuels. For those reasons, this study offers the first complete assessment of the potential of biofuels in Latin America and the Caribbean for 28 countries in the region, based on 12 agricultural and forestry crops. We first identify the biofuel production potential based on current surplus production, as a catalyst of biofuel production in the region. We then estimate the land requirements based on a 5% replacement of domestic liquid fuel demand, and the suitable available area in each country for such replacement. We also project biofuel production and available land area needed to meet food and nutrition targets for countries in the region to 2025. The results of this study show that the crops with the largest potential in Latin America and the Caribbean are sugar canes and cassava. Based on current production levels the conversion of sugar cane into bioethanol could surpass the 5% mix in more than half of the domestic markets of the countries surveyed. For biodiesel, countries with current surplus production that could be transformed to biodiesel and exceed the 5% mix include Argentina, Bolivia, Paraguay, Costa Rica and Honduras. For land, Latin America, particularly South America may have enough suitable land for production of biofuels, specially sugar cane, soybeans and oil palm, the main crops identified in this study. As for food supply and security and the future production of biofuels to 2025, we find that for major food exporters, there is enough land for both food and energy crop production. However, there are some smaller countries, especially in Central America and the Caribbean that may have to decide whether to import food and produce energy from crops. In term of the effect on prices, we find that increased biofuel production may have important price effects the effect may depend we analyze energy crops, traditional crops or byproducts of biofuel production. Finally, in terms of the impact on agricultural structure and land ownership, the most significant structural changes consist in a higher concentration in production and tenure as well as the establishment of new kind of actors and norms. Policies and institutions should be established that enables small producers to take advantage of increased biofuel production, so they can benefit in terms of employment, income, as means for poverty reduction in rural areas of Latin America and the Caribbean.

This paper projects global food supply and demand to the year 2025, with a particular emphasis on Asia. Technological change is found to be the critical factor in determining whether or not food prices will preserve their long-run, downward trend, as well as the likely patterns of trade and structural change. Historical and projected rates of total factor productivity (TFP) growth are decomposed into outward movement in the frontier and "catching up" to the world frontier. Overall, the baseline scenario reduces the poverty headcount ratio in People's Republic of China (PRC) by more than 80 percent. In the Association of Southeast Asian Nations (ASEAN) it falls by about 40%. However, in South Asia, the falling headcount ratio (17%) is insuffi cient to lower aggregate poverty, due to the relatively strong rise in the region's population. In the baseline projections, crop productivity in the ASEAN region declines by 0.4%/year. This refl ects decades of neglect in research expenditures. In an alternative scenario, future ASEAN crop TFP is raised to the Asia-wide rate of 0.95%/year. This alternative scenario boosts production in nearly all sectors of the economy, and lowers the poverty headcount ratio by an additional 14%. This could be expected to lift more than 30 million additional people out of poverty in the ASEAN region.

For the past two years the United States and Colombia, Peru and Ecuador have being negotiating a Free Trade Agreement (FTA). One of the main concerns of Ecuador's farmers is the asymmetry that exists between U.S. and Ecuador agricultural sectors. U.S. agriculture is highly subsidized in products such as rice, corn, and soybeans, products that represent an important export and subsistence products for Ecuadorian farmers. To reduce any negative effect that the FTA may have, Ecuador's government is studying land-based payments for rice, corn, soybeans and livestock producers. This program would offer direct initial support to farmers' income after the FTA enters in full effect. The objectives of this paper were twofold. First, estimate the effects on the Ecuadorian economy, and especially on Ecuador's agriculture of the FTA. And second, study the viability of the domestic support program for agriculture proposed by the Ecuadorian government, as well as some alternative domestic support policies. We use a modified version of the GTAP global general equilibrium model specific for agriculture support, called GTAP-AGR. The results show that trade liberalization will negatively affect all agricultural sectors in Ecuador, except for the exporting sectors (bananas, coffee, cocoa, and flowers). Government subsidies are estimated to disproportionally help rice and soybeans producers, but they will not be enough for corn and livestock producers. We conclude that government subsidies should be extended to other sector such as sugar cane and cotton.

There is considerable interest in projections of future productivity growth in agriculture. Whether one is interested in the outlook for global commodity markets, future patterns of international trade, or the interactions between land use, deforestation and ecological diversity, the rate of productivity growth in agriculture is an essential input. Yet solid projections for this variable have proven elusive – particularly on a global basis. This is due, in no small part, to the difficulty in measuring historical productivity growth. The purpose of this paper is to report the latest time series evidence on total factor productivity growth for crops, ruminants and non-ruminant livestock, on a global basis. We then follow with tests for convergence amongst regions, providing forecasts for farm productivity growth to the year 2040. The results suggest that most regions in the sample are likely to experience larger productivity gains in livestock than in crops. Within livestock, the non-ruminant sector is expected to continue to be more dynamic than the ruminant sector. Given the rapid rates of productivity growth observed recently, non-ruminant and crop productivity in developing countries may be converging to the productivity levels of developed countries. For ruminants, the results show that productivity levels may be diverging between developed and developing countries.

In this study we evaluate the effect of annual productivity growth in agriculture over the 1991-2001 period on poverty in eleven developing countries. We compare this with the optimal pattern of productivity growth of comparable cost with the sole goal of maximizing poverty reduction. This comparison reveals that regional agricultural development is a viable option in the fight for poverty reduction.

Limited data on the allocation of inputs to different activities has limited agricultural economists' attempts to measure sub-sector productivity growth in agriculture. However, recent developments have enabled us to estimate total factor productivity (TFP) growth for crops and livestock accounting for input-output allocation. This paper extends previous work on TFP measurement for livestock into ruminants and non-ruminant productivity measurement, given the differences in productivity growth rates among these species. The results show that the non-ruminant sector is more dynamic than the ruminant sector, driving most of the productivity growth within the livestock sector. Given the rapid rates of productivity growth observed recently, non-ruminant productivity in developing countries may soon be converging to the productivity levels of developed countries.

World food trade patterns have changed in the last 40 years with the share of world trade comprised of bulk commodities falling, and the share of world food trade comprised of processed commodities rising. These changes have been driven by a combination of supply and demand forces. On the demand side, world demand for livestock products and more highly processed food products has been rising more rapidly than that for bulk products. This increasing demand can either be met from domestic production or from foreign production in the latter case resulting in increased international trade. The extent to which the increased demand can be met from domestic production depends importantly on the rate of productivity growth in the various components of the farm and food sector. This is why the relative rates of productivity growth in crops and livestock is also believed to be an important factor in determining the changing composition of trade. This study seeks to understand to what extent productivity growth in crops and livestock has affected world food trade patterns. We do so by first estimating total factor productivity growth in crops and livestock over the past four decades. The results show that productivity growth in crops has been larger in developed countries. However, non-ruminant productivity growth in developing countries has been larger. By incorporating these estimates into a back-casting exercise with the GTAP general equilibrium model, we hope to understand how these differential productivity growth rates have influenced the composition of world food trade.

Increased domestic concentration and international competition in the floricultural industry are forcing growers to improve resource management efficiency. Cost management and cost accounting methods are becoming key tools as growers attempt to reduce costs. These tools allow growers to allocate costs for each crop, increasing their greenhouse planning abilities. Growers have a relative high degree of risk due to potential crop and market failure. Individual growers have different tolerance for risk and risk bearing capacity. Growers need a cost accounting system that incorporates production and market risk, a system that allows them to make informed business decisions. The research reported in this paper developed a greenhouse budgeting model that incorporated risk to allow growers to compare production costs for flowers with different genetics and production technologies. This enables greenhouse growers to make production management decisions that incorporate production and market risk. The model gives growers the option of imputing their own production data to evaluate how various yield and price assumptions influence income and expense projections, and ultimately, profit. The model allows growers to compare total production cost and revenue varying grower type, production time, geographical location, operation size, and cost structure. The model evaluates budgets for growers who market to mass-market retail operations or wholesale intermediaries who sell to merchandisers or flower shops distribution channels. The model was demonstrated with sample data to illustrate how incorporating risk analysis into a grower's greenhouse budget model effects resource allocation and production decisions as compare to a budget model that does not incorporate risk. Deterministic and stochastic models were used to demonstrate differences in production decisions under various assumptions. The stochastic model introduced prices and flowering characteristics variability. The @Risk software was used to generate the random number simulation of the stochastic model, and stochastic dominance analysis was used to rank the alternatives. The result for both the deterministic and stochastic models identified the same cultivar as most profitable. However, there were differences in crop profits levels and rankings for subsequent cultivars that could influence growers' production choice decisions. The grower's risk aversion level influenced his/her choice of the most profitable cultivars in the stochastic model. The model summarizes the sources of variability that affect cost and revenue. The model enables the grower to measure effects that change in productivity might have on profit. Growers can identify items in their budget that have a greater effect on profitability, and make adjustments. The model can be used to allocate cost across activities, so the grower would be able to measure the economic impact of an item on the budget.