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Maize is a staple crop and underpins food security for Zambia. Maize productivity in Zambia is almost half the potential due to low uptake of conservation agricultural practices. This study tests the hypothesis of the trade-offs between agriculture productivity and long-term ecosystem services (ES) provision among maize farmers practising conventional agriculture on the one hand, and those practising conservation agriculture on the other hand, in Kafue district, Zambia. In addition, challenges which affect conservation agriculture uptake are assessed. Besides these challenges, the study notes that adoption of a new technology is also influenced by its efficiency, and therefore technical efficiency scores were estimated using the Stochastic Frontier Approach (SFA) to compare efficiency levels of the two agricultural systems. Kafue was purposefully selected as it is among the first districts where conservation agriculture was introduced. Through purposive and random sampling, the households surveyed were split into two distinct groups namely conservation agriculture (CA) farmers (treatment group) and conventional agriculture (CV) farmers (control group). The analysis significantly shows that farmers practicing CA have more knowledge than CV farmers about the capacity of conservation agriculture to reduce soil erosion, increase soil fertility, retain nutrients, mitigate pests and weeds and increase crop yield. However, both farming groups knew that CA helps conserve soils and that soil maintenance is important for food production. On the other hand, significantly, CV farmers knew more than CA farmers that CV reduces crop yield and increases soil erosion. On the other hand, CV farmers expressed a higher level of willingness to adopt CA practices than CA farmers who are unwilling to expand their area under CA. The study further shows that at least 55% of farmers practicing CA find inadequate labour to be the main challenge faced in CA. It appears that a policy that improves the farmers' knowledge on CA would help improve the uptake of CA. CA farmers were significantly more knowledgeable than CV farmers about the detrimental effects of CV, such as increasing air and water pollution, thus raising the need for training among CV farmers with emphasis on the effects of their farming system on the environment which affect the supply of ecosystem services. Efficiency is also a means of improving productivity hence the Stochastic Frontier Analysis (SFA) was employed to estimate technical efficiency levels in maize production. Using SFA, the study found that the technical efficiency of maize among CV farmers is 71.3% on average while that of CA farmers is 57.9% on average. Moreover, the study found that there was a significant difference (t=3.9854, P=0.0002) in the technical efficiency scores of the both CV and CA farmers. Nevertheless, the study also found that 77% of output variation among CA farmers can be explained by variation in technical efficiency. However, 33.4 % of total maize output can be explained by variation in technical efficiency among CV farmers. This means that CA farmers have a higher potential to increase their current output than CV farmers. Finally there was no significant difference in fertiliser usage between CA and CV farmers (t=1.3825, P=0.1700). Further, from SFA fertiliser responsiveness to maize output showed that a 1% increase in the use of synthetic fertiliser leads to 0.678% and 0% increase in maize output per hectare for CA and CV respectively at both 1% and 10% level of significance at the expense of water and air quality. Therefore, it can be concluded that there is a higher trade-off between maize production and water and air quality under conventional than under conservation agriculture. / Dissertation (MSc (Agric))--University of Pretoria, 2016. / Agricultural Economics, Extension and Rural Development / MSc (Agric) / Unrestricted

About 75% of human food in the 21st century consists of just 12 crops, though specific crops vary among nations. Modern technology has allowed development of innovative food and non-food uses for these commodities. For instance, corn (maize (Zea mays L.)) is produced for many purposes, including food, livestock feed, biofuels, fiber for clothing, etcetera. Scientists project the human population will reach 9.2 billion in next 20 years—an 18% increase from the 2020 population of 7.8 billion—resulting in increased demand for corn and other crops. Hence, farmers must increase total crop production to meet demand; however, local agricultural resource endowments such as climate, land and water availability, and soil attributes constrain production. Perhaps the quickest yield and efficiency improvements will result from farm management practices that tailor input applications to match accurate seasonal weather forecasts. Regional seasonal weather forecasts would enable farmers to optimize yields by reducing yield risk from extreme weather events, as well as from less extreme inter-annual weather variability. Improved productive efficiency is also critical to reducing environmental harms, e.g. contaminated runoff from excessive agricultural input use. The objective of this dissertation is to estimate the corn yield frontier and efficiency measures based on agricultural input management and weather. This research contributes to an enhanced understanding of how the corn yield frontier responds to inter-annual weather variations, and how it may shift with climate change. The first chapter summarizes three main topics—farm technology, climate change and weather variability, and methods for evaluating production efficiency. The second presents estimated corn yield frontiers and efficiency measures based on stochastic frontier and data envelopment analyses for nine North Dakota Agricultural Statistics Districts from 1994 to 2018. The third presents corn yield efficiency measures for five states: Minnesota, North Dakota, Nebraska, South Dakota, and Wisconsin from 1994 to 2018. The results reveal the major causes of inter-annual yield variation are variability of rainfall and temperature. Development of accurate growing-season weather forecasts is likely to result in high value-added for farmers and downstream agribusinesses. Federal, state, and private research funding in seasonal weather forecasting would probably be well invested.

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Magister Economicae - MEcon / Despite its recent remarkable economic growth, Ethiopia remains one of the poorest countries in the world. More than 80 percent of Ethiopians obtain their livelihood from traditional low-productivity agricultural activities. Due to lack of water storage facilities and the erratic nature of rainfalls, most farmers don’t have access to water to produce more than one crop per year and hence there are frequent crop failures due to droughts which have made the country one of the highest food insecure nations and receiver of food aid. It is evident that a comprehensive effort is required to increase crop and agricultural production through different intensification and productivity enhancement mechanisms and reduce rural household’s food insecurity and poverty. In line with this the Government of Ethiopia and different NGO’s have been promoting irrigation technology as a viable option in enhancing farm productivity and efficiency improvements.By integrating field observations, economic theory, and econometric analysis, this study assess the extent to which access to irrigation technology affects the level of technical efficiency in Gorogutu district of Eastern Ethiopia. The analysis is based on primary household-level data collected from 100 randomly selected households in 20010/11 cropping season. To analyze the effect of the technology on technical efficiency, three different Cobb-Douglas type of Stochastic Production Functions were estimated. More so, to explore different socio- economic and institutional determinants of technical efficiency in the study district, an inefficiency effect model was estimated using the one step procedure.The result from the estimated models has shown that farm households in the study area are not technically efficient and there is a chance to increase output by using the technology and mix of production input used by the best farm household (with 20 percent technical inefficiency). In addition, it also showed that households with access to irrigation technology are more technically efficient (84 percent technical efficiency) than those without access to the technology (77 percent technical efficiency). And household’s access to irrigation technology, access to extension service and distance travelled from farm plot to homestead are a significant determinant of technical efficiency in the study area.The study recommended, among other things, as a country that has a huge potential for irrigation development, utilization of this potential and providing irrigation technology to farm households will have a huge impact on the livelihoods of the majority of the poor. Evidently, efforts tailored towards this end would be very essential in militating against the high levels of poverty that is persistent in the communities

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Doctor of Philosophy / Department of Agricultural Economics / Jeffrey M. Peterson / This study focused on the economic efficiency of Kansas farms. The goal was to investigate factors and how they might affect farms and their economic and production performance. Kansas was selected as the region of study for its large agricultural production and distinctive type of multiple-operation farms. Farms in the sample could produce three outputs, crops, livestock and custom work. Inputs for the farms included measures of capital, labor, land and purchased inputs. Production outputs were measured in bushels and tons; input quantities were computed from input expenditures applying an input price index taken from the US Department of Agriculture in real US dollars. The dataset consisted of a 10-year (1998-2007) panel of 456 multi-output farms belonging to the Kansas Farm Management Association (KFMA). Data Envelopment Analysis (DEA) techniques were used to construct a non-parametric efficiency frontier and calculate technical efficiency (TE), allocative efficiency (AE), scale efficiency (SE), and overall or economic efficiency (OE) for each farm and each year. A discretionary input oriented DEA technique was used to assess the effect of capital availability as a farm input and its impact on farms' efficiencies. Efficiency scores in this problem were compared to the farms' scores when the level of debt was accounted for as a farm input. Panel data Tobit analysis was applied to the farms' inefficiency scores to investigate the causality of selected farm characteristics on technical, allocative, scale and overall inefficiencies. For the sampled farms and period, results confirmed that larger farms were more efficient than smaller ones. Farms specializing in livestock products, such as dairy and beef, were reported to be slightly more overall efficient than crop or mixed farms. Some economies of scope were found between custom work operations and crops. Financial structure of the farms was measured using the ratio of total debt to total assets for each farm. According to the results, larger leverage ratios increased all farm efficiencies. The positive effect of debt or capital availability in Kansas farms efficiencies was confirmed. The results of the technical efficiency discretionary DEA model agreed with this finding.

The thesis examines technical efficiency using frontier efficiency estimation techniques from parametric and non-parametric approaches. Five different frontier efficiency estimation techniques are considered which are SFA, DFA, DEA-CCR, DEA-BCC and DEA-RAM. These techniques are then used on an artificially generated panel dataset using a two-input two-output production function framework based on characteristics of German life-insurers. The key contribution of the thesis is firstly, a study that uses simulated panel dataset to estimate frontier efficiency techniques and secondly, a research framework that compares multiple frontier efficiency techniques across parametric and non-parametric approaches in the context of simulated panel data. The findings suggest that, as opposed to previous studies, parametric and non-parametric approaches can both generate comparable technical efficiency scores with simulated data. Moreover, techniques from parametric approaches, i.e. SFA and DFA are consistent with each other whereas the same applies to non-parametric approaches, i.e. DEA models. The research study also discusses some important theoretical and methodological implication of the findings and suggests some ways whereby future research can enable to overcome some of the restrictions associated with current approaches.

Attainment of greater efficiency in hospital operations has become a goal highly sought after as a result of several factors including skyrocketing costs. The possibility that the different incentives associated with ownership type might affect efficiency has been covered thoroughly in the literature. There are numerous studies comparing for-profit to not-for-profit hospitals or public to private hospitals. Analysis of federal ownership, however, has been less studied. In particular, comparisons involving military hospitals are non-existent, attributed to data availability and an assumption that military hospitals are too different from civilian facilities. This dissertation employs a cross-sectional Stochastic Frontier Analysis (“SFA”) of 2006 data to compare the technical efficiency of military, for-profit, not-for-profit, and other government hospitals, controlling for differences in patients, scope of work, physicianhospital working arrangements, and other structural characteristics. Four model specifications are examined, varying the method of accounting for heterogeneity of case mix. One of the specifications uses a distance function technique to allow for specific inclusion of multiple outputs, namely inpatient and outpatient workload. Results obtained using SFA are validated using Data Envelopment Analysis (“DEA”) and compared with results produced through simple ratio analysis. Estimates of overall technical efficiency ranged from 76% to 80%. The analysis found no significant correlation between ownership category and technical efficiency. Factors found to be significantly correlated with greater technical efficiency include younger average patient age, more female patients, percentage of surgical inpatient work, percentage of circulatory system-based work, accreditation, and having all credentialed physicians (i.e. no physician employees). Pooled-vs.-partitioned analysis showed that military hospitals are indeed different, but not enough to render comparisons meaningless. Data Envelopment Analysis produced comparable individual hospital efficiency scores (correlations of approximately 0.6 between like specifications using SFA and DEA) and comparable average efficiency (~87%). Ratio analysis results were sensitive to the specific ratio analyzed. This dissertation adds to the body of literature on the relationship between ownership and hospital technical efficiency. It is the first comparison of military and civilian hospital technical efficiency.

This thesis deals with the globalization of production, a salient feature of the modern economy. The development of international outsourcing as a widespread business practice and the simultaneous decrease in trade and transport costs have contributed to the growth of a phenomenon known as global value chains. The main aim of the thesis is to understand how global value chains alter the location of economic activity. The thesis also studies the extent of firms' participation in global value chains and its consequences for firm performance.   The thesis consists of four papers studying the behavior of firms in global value chains. Paper 1 analyzes how production fragmentation influences the importing and exporting behavior of Swedish firms in the manufacturing sector. Paper 2 focuses on manufacturing firms in the ICT sector and analyzes the effect of global sourcing on firm performance. In Paper 3, the thesis examines deeper implications of global production by investigating whether exposure to trade raises firms' sensitivity to external shocks. The final paper in the thesis studies the location patterns of multinational firms and analyzes the effect of institutional distance on the number of multinational entries in developing countries.   A number of patterns emerge from these studies. The first is that Swedish manufacturing firms increasingly participate in global value chains by sourcing production inputs from overseas to create products for local and foreign customers. As a result, global value chains help to alter the specialization patterns of manufacturing firms. The second finding is that firms reap benefits from global sourcing in the form of greater efficiency. However, global sourcing may also raise the responsiveness of firms to negative external shocks. The final key result points to a developing trend in the location of activity in which emerging market multinational firms are becoming significant sources of foreign direct investment flows and their investment patterns challenge existing theories of multinational location choice.