Master of Science / Department of Agricultural Economics / Timothy Dalton / Previous research in low-income countries reveals that genetically modified (GM) maize has the potential to increase yield and reduce labor use; however, other issues, especially regarding Roundup Ready (RR) maize, remain mostly unexplored. This research examines the impact of GM maize on yield, cost, and risk among 184 smallholders during the 2009-10 maize production season in two regions in KwaZulu-Natal, South Africa; Hlabisa and Simdlangetsha. Two hybrid maize varieties; Pannar and Carnia, and three GM varieties; Bt, RR, and BR (stacked with Bt and RR) are produced. In both regions, producers of RR and BR maize pay 47% more per kilogram of seed and use 44% less labor per hectare compared to other varieties. Due to low labor costs, net returns from RR and BR varieties are 25% and 40% higher than other varieties in Hlabisa and Simdlangetsha, respectively. Stochastic dominance analysis is used to compare net returns of all five varieties in both regions. RR maize is second-degree stochastic dominant to all other varieties in Simdlangetsha, while no variety is stochastically dominant in Hlabisa. Stochastic efficiency with respect to a function (SERF) analysis indicates that RR maize is the preferred variety for producers over the entire range of risk preferences in both regions. While average maize gross returns are $713 per hectare, risk premiums between $18 and $221 must be paid to RR maize producers, depending on region and farmer risk preference, to persuade them to switch to the second-most preferred variety. Econometric analysis indicates significant yield gains of at least 8% from RR maize, although the yield gain varies greatly when input endogeneity is taken into account. Elasticities of output with respect to labor are 0.41 and 0.82 for RR and non-RR maize respectively, and 0.61 and 0.33 with respect to land. A cost function analysis indicates that RR maize has 19% lower costs per maize plot, which increases to at least a 35% advantage when controlling for selectivity bias. Nonparametric kernel density estimation also reveals consistently lower total and average costs of RR maize at most levels of output, suggesting technological benefits to smallholder farmers from RR maize not available through conventionally-bred hybrids.

Cette thèse présente l’étude d’un problème de contrôle optimal dont le coût est non-différentiable pourcertaines valeurs du contrôle ou de l’état, tout en restant Lipschitz. Ce problème nous a été inspiré par laproblématique générale de la minimisation de l’énergie dépensée par un véhicule ou robot de type voiture lelong d’un trajet dont le profil de route est connu à l’avance. Cette problématique est formulée à l’aide d’unmodèle simple de la dynamique longitudinale du véhicule et une fonction coût qui englobe la notiond’efficacité du processus de conversion énergétique. Nous présentons un résultat de régularité des contrôles,valable pour la classe des systèmes non-linéaires, affines dans les contrôles, classe à laquelle appartient notreproblème. Ce résultat nous permet d’exclure les phénomènes de chattering de l’ensemble des solutions. Nousréalisons trois études de cas pour lesquelles les trajectoires optimales sont composées d’arcs bang,d’inactivations, d’arcs singuliers et, dans certains cas, de retours en arrière. / The present thesis is a study of an optimal control problem having a non-differentiable, but Lipschitz, costfunction. It is inspired by the minimization of the energy consumption of a car-like vehicle or robot along aroad which profile is known. This problem is stated by means of a simple model of the longitudinal dynamicsand a running cost that comprises both an absolute value function and a function that accounts for theefficiency of the energy conversion process. A regularity result that excludes chattering phenomena from theset of solutions is proven. It is valid for the class of control affine systems, which includes the consideredproblem. Three case studies are detailed and analysed. The optimal trajectories are shown to be made of bang,inactivated and backward arcs.

The EU has been promoting unbundling of the transmission grid from other stages of the electricity supply chain with the aim of fostering competition in the upstream stage of electricity generation. At present, ownership unbundling is the predominant form of unbundling in Europe. From a policy perspective, a successful unbundling regime would require that the benefits of increased competition in power generation would at least offset the associated efficiency losses from vertical divestiture. Since evidence on this topic is scarce, this study helps fill this void by empirically estimating the magnitude of economies of vertical integration (EVI) between electricity generation and transmission based on a quadratic cost function. For this purpose we employ unique firm-level panel data of European electricity utilities. Our results confirm the presence of substantial EVI of 14% for the median sized integrated utility. Moreover, EVI tend to increase with firm size.

Work-related disorders due to biomechanical exposures have been subject to extensive research. Studies addressing these exposures have, however, paid limited attention to an efficient use of resources in exposure assessment. The present thesis investigates cost-efficient procedures for assessment of work-related biomechanical exposures, i.e. procedures aiming at a proper balance between statistical and economic performance. Paper I is a systematic review of tools used in literature providing cost-efficient data collection designs. Two main approaches were identified in nine publications, i.e. comparing cost efficiency among alternative data collection designs, and optimizing resource allocation between different stages of data collection, e.g. subjects and samples within subjects. The studies presented, in general, simplified analyses, in particular with respect to economics. Paper II compared the cost-efficiency of four video-based techniques for assessing upper arm postures. The comparison was based both on a comprehensive model of cost and error and additionally on two simplified models. Labour costs were a dominant factor in the cost efficiency comparison. Measurement bias and costs other than labour cost influenced the rank and economic evaluation of the assessment techniques. Paper III compared the cost efficiency of different combinations of direct and indirect methods for exposure assessments. Although a combination of methods could significantly reduce the total cost of obtaining a desired level of precision, the total cost was, in the investigated scenario, lowest when only direct measurements were performed. However, when the total number of measurements was fixed, a combination was the most cost efficient choice. In Paper IV, demand functions were derived for a four-stage measurement strategy with the focus of either minimizing the cost for a required precision, or maximizing the precision for a predetermined budget. The paper presents algorithms for identifying optimal values of measurement inputs at all four stages, adjusted to integers, as necessary for practical application. In summary, the thesis shows that it is important to address all sources of costs and errors associated with alternative measurement designs in any particular study, and that an optimal determination of samples at different stages can be identified in several cases not previously addressed in the literature.

Submitted by Clebson Anjos (clebson.leandro54@gmail.com) on 2016-02-15T20:03:45Z No. of bitstreams: 1 arquivototal.pdf: 2424729 bytes, checksum: 0b742be3286a70e0901c3d5a00813f6f (MD5) / Made available in DSpace on 2016-02-15T20:03:45Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2424729 bytes, checksum: 0b742be3286a70e0901c3d5a00813f6f (MD5) Previous issue date: 2015-08-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / One of the main issues related to the mobile robotics area is to find the most efficient way to perform the navigation from one point to another over environments, considering maximum safety and spending as less as possible time and computer resources. From this perspective, the aim of this work was to specify improved heuristics that could be applicable to cost functions of key A* based algorithms and use, more efficiently, the available computational resources. In this way, our approach aimed at minimizing the amount of collisions, the length of paths, and the processing time by minimizing the importance of g(n) term, which accounts for storing information from past steps of A* family algorithms. To show the effects of this modification, a survey of the best search strategies in dynamic and static environments was carried out and, after that, we analyzed the four best and latest algorithms, according to the specialized literature. Some comparisons have been made considering static and highly dynamic environments with different directions and search parameters to measure the quality of generated paths. Then, these algorithms were again analyzed with their cost functions modified according to our approach. The results of the comparison show that the R* algorithm, with forward search, is the most efficient for different spaces and searches. However, the change in their respective cost functions provided a significant improvement in the already excellent results achieved by the algorithms. In static environments, this modification showed up to be more effective for large and complex problems, which are commonly used for real robots. In highly dynamic environments, the cost function modification provided a considerable reduction in the time of planning and number of iterations to find the goal, as well as reductions in the memory utilization. / Uma das principais questões relacionados ao tema da robótica móvel é descobrir a maneira mais eficiente para realizar a navegação, de um ponto a outro no ambiente, com máxima segurança e despendendo a menor quantidade de tempo e de recursos computacionais possível. À vista disso, o presente trabalho se motiva a desenvolver uma melhoria heurística que possa ser aplicável às funções custo dos principais algoritmos baseados na família A* e que propõe utilizar, de forma mais eficiente, os recursos computacionais disponíveis, aperfeiçoando assim, os resultados obtidos através dos principais algoritmos de buscas aplicados à robótica móvel. A mesma tem o objetivo de minimizar a quantidade de colisões, a duração do trajeto, bem como o tempo de processamento através da minimização da importância da variável g(n) - responsável em armazenar informações subutilizadas do passado dos algoritmos. Para visualizar os efeitos dessa modificação, um levantamento das melhores estratégias de busca em ambiente estático e dinâmico foi realizado e, através deste, foram analisados os quatro melhores e mais atuais algoritmos destacados pela literatura técnica especializada. Algumas comparações foram efetuadas considerando ambientes estáticos e altamente dinâmico com diferentes direções de busca e parâmetros que visavam mensurar a qualidade das trajetórias geradas. Em seguida, esses foram novamente analisados com suas respectivas funções custo modificada. Os resultados da comparação demonstraram que o algoritmo R*, com direção de busca direta, é o mais eficiente para diferentes espaços e pesquisas. No entanto, a modificação em suas respectivas funções custo proporcionou uma melhora significativa nos resultados conquistados pelos algoritmos originais. Em ambientes estáticos, esta modificação se mostrou mais eficaz para problemas grandes e complexos, os que são efetivamente utilizados por robôs reais. Em ambientes altamente dinâmicos, a mesma apresentou uma redução considerável no tempo de planejamento e no número de iterações para localizar o objetivo, bem como reduziu a utilização de memória o que, consequentemente, tornou os robôs mais ágeis e habilidosos.

The diploma thesis deals with cost analysis, determination of cost functions, cost evaluation and creation of proper model of solution. It compares theoretical knowledge with reality in society, specifies possibilities of their changes and techniques used to optimize costs. The analyzed company – ABB s.r.o.

Present research into critical embedded control systems tends to focus on the computational elements and largely ignore the link between the computational and physical elements. This link is very important since the computational capability of the computer can greatly affect the performance and dynamics of the system it controls. The control computer is in the feedback loop of control systems and contributes to feedback delay in addition to already existing mechanical delays. While mechanical delays are compensated in control design, variable computational delays cause system to underperform in its intended physical behavior and impose a cost in terms of fuel or time. For this reason, the scheduler in a real-time operating systems should not focus only on the task deadlines, but also on efficient scheduling which minimizes the effect of computational delay on the controlled plant. The proposed work provides a systematic framework to manage and evaluate the implications of computational delay in vehicles. The work also includes cost sensitive real-time control task scheduling heuristics and Dynamic Voltage Scaling (DVS) for better energy/thermal control. We show through simulations that our heuristic achieves a significant improvement in cost over the traditional real-time scheduling algorithm Earliest Deadline First (EDF) and show that it can adjust according to energy constraints imposed on the system.

This dissertation studies decision theories for both individual and interactive choice problems. This thesis proposes three non-standard models that modify assumptions and settings of standard models. Chapter 1 provides an overview of this dissertation. In the second chapter I present a model of decision-making under uncertainty in which an agent is constrained in her cognitive ability to consider complex acts. The complexity of an act is identified by the corresponding partition of state space. The agent ranks acts according to the expected utility net of complexity cost. I introduce a new axiom called Aversion to Complexity, that depicts an agent's aversion to complex acts. This axiom, together with other modified classical expected utility axioms characterizes a Complexity Aversion Representation. In addition, I present applications to competitive markets with uncertainty and optimal contract design. The third Chapter discusses how a complexity averse agent measures the complexity cost of an act after she receives new information. I propose an updating rule for the complexity cost function called Minimal Complexity Updating. The idea is that if the agent is told that the true state must belong to a particular event, she needs not consider the complexity of an act outside of this event. The main result characterizes axiomatically the Minimal Complexity Aversion Representation. Lastly, I apply the idea of Minimal Complexity Updating to the theory of rational inattention. The last chapter deals with a variant model of fictitious play, in which each player has a perturbation term that measures to what extent his rival will stick to the rules of traditional fictitious play. I find that the empirical distribution can converge to a pure Nash equilibrium if the perturbation term is bounded. Furthermore, I introduce an updating rule for the perturbation term. I prove that if the perturbation term is updated in accordance with this rule, then play can converge to a pure Nash equilibrium. / Doctor of Philosophy / This dissertation studies decision theories for both individual and interactive choice problems. This thesis proposes three non-standard models that modify assumptions and settings of standard models. Chapter 1 provides an overview of this dissertation. In the second chapter I present a model of decision-making under uncertainty in which an agent is constrained in her cognitive ability to consider complex acts. The complexity of an act is identified by the corresponding partition of state space. The agent ranks acts according to the expected utility net of complexity cost. I introduce a new axiom called Aversion to Complexity, that depicts an agent's aversion to complex acts. This axiom, together with other modified classical expected utility axioms characterizes a Complexity Aversion Representation. In addition, I present applications to competitive markets with uncertainty and optimal contract design. The third Chapter discusses how a complexity averse agent measures the complexity cost of an act after she receives new information. I propose an updating rule for the complexity cost function called Minimal Complexity Updating. The idea is that if the agent is told that the true state must belong to a particular event, she needs not consider the complexity of an act outside of this event. The main result characterizes axiomatically the Minimal Complexity Aversion Representation. Lastly, I apply the idea of Minimal Complexity Updating to the theory of rational inattention. The last chapter deals with a variant model of fictitious play, in which each player has a perturbation term that measures to what extent his rival will stick to the rules of traditional fictitious play. I find that the empirical distribution can converge to a pure Nash equilibrium if the perturbation term is bounded. Furthermore, I introduce an updating rule for the perturbation term. I prove that if the perturbation term is updated in accordance with this rule, then play can converge to a pure Nash equilibrium.

This doctoral thesis consists of three essays. In the first essay I investigate the presence of productivity convergence in eight regional pulp and paper industries of U.S. and Canada over the period of 1971-2005. Expectation of productivity convergence in the pulp and paper industries of Canadian provinces and of the states of its southern neighbour is high since they are trading partners with fairly high level of exchanges in both pulp and paper products. Moreover, they share a common production technology that changed very little over the last century. I supplement the North-American regional data with national data for two Nordic countries, Finland and Sweden, which provides a scope to compare the productivity performances of four leading players in global pulp and paper industry. I find evidence in favour of the catch-up hypothesis among the regional pulp and paper industries of U.S. and Canada in my sample. The growth performance is at the advantage of Canadian provinces relative to their U.S. counterparts. However, it is not good enough to surpass the growth rates of this industry in the two Nordic countries. It is well-known that econometric productivity estimation using flexible functional forms often encounter violations of curvature conditions. However, the productivity literature does not provide any guidance on the selection of appropriate functional forms once they satisfy the theoretical regularity conditions. The second chapter of my thesis provides an empirical evidence that imposing local curvature conditions on the flexible functional forms affect total factor productivity (TFP) estimates in addition to the elasticity estimates. Moreover, I use this as a criterion for evaluating the performances of three widely used locally flexible cost functional forms - the translog (TL), the Generalized Leontief (GL), and the Normalized Quadratic (NQ) - in providing TFP estimates. Results suggest that the NQ model performs better than the other two functional forms in providing TFP estimates. The third essay capitalizes on newly available high frequency energy consumption data from commercial buildings in the District of Columbia (DC) to provide novel insights on the realized energy use impacts of energy efficiency standards in commercial buildings. Combining these data with hourly weather data and information on tenancy contract structure I evaluate the impacts of energy standards, contractual structure of utility bill payments, and energy star labeling on account level electricity consumption. Using this unique panel dataset, the analysis takes advantage of detailed building-level characteristics and the heterogeneity in the building age distribution, resulting in buildings constructed before and after mandatory energy standards came into effect. Estimation results suggest that in commercial buildings constructed under a code, electricity consumption is lower by about 0.48 kWh per cooling degree hour. When tenants pay for their own utilities, consumption is lower by 0.82 kWh per cooling degree hour. The Energy Star effect is a 0.31 kWh reduction per cooling degree hour. Finally, peak savings for all three variables of interest occur at 2pm in the summer months, whereas peak summer marginal prices at DC's local electric utility occur at 5pm.

The purpose of the thesis is to introduce novel measure of real marginal cost in the New Keynesian Phillips Curve (NKPC) and compares its performance with conventional mea- sures such as output gap and labour share of income. Real marginal cost is derived from a flexible function whereas labour share is based on restrictive assumption of Cobb-Douglas technology. Dynamic correlations and results of NKPC indicate that real marginal cost is better than ad hoc measure of output gap and labour share. Given the heterogeneity in price setting behaviour across sectors, cost functions and NKPC are estimated for the agriculture, manufacturing and other sectors of Pakistan's economy. Real marginal cost is derived from static and dynamic cost functions. In the presence of adjustment costs, dynamic cost functions that are consistent and integrated with their static systems are required. Such dynamic translog cost functions are estimated after testing the theoretical properties and existence of long term relationships in the static functions. Cost attributes, marginal cost, total factor productivity, technological progress, demand and substitution elasticities are derived from static and dynamic functions. Three specifications of forward looking and hybrid form of the Phillips curves are estimated with real marginal cost, output gap and labour share. Results indicate that hybrid specifications perform better than the forward looking models in terms of goodness of fit and statistical significance. Further, comparison of Phillips curves estimated with real marginal cost, output gap and labour share indicate that real marginal cost performs better in explaining inflation dynamics in Pakistan. The results indicate that forward looking behaviour dominates and high level of nominal rigidities persists in Pakistan. Finally, hybrid form of the NKPC is estimated for a panel of sixteen Asian economies. With the consideration of heterogeneity and aggregation bias, the mean group, random coefficient and weighted average coefficients are derived from individual estimates. The unobserved time variant common factors cause cross correlation in the errors that may lead towards inconsistent estimates. Therefore, cross section averages of the explanatory and the dependent variables are augmented in hybrid specification to capture the effect of latent variables. Findings suggest that the discount factor is almost 0.94, the nominal rigidities are 33% and the weights of expected and past inflation are 66% and 33% respectively. Nominal rigidities of the Asian economies are lower than the estimates for US and Euro areas. The weights of expected and past inflation of the Asian economies are consistent with the US but lower than the estimates from the Euro areas.