Stein factors for negative binomial approximation in Wasserstein distance

The paper gives the bounds on the solutions to a Stein equation for the negative binomial distribution that are needed for approximation in terms of the Wasserstein metric. The proofs are probabilistic, and follow the approach introduced in Barbour and Xia (Bernoulli 12 (2006) 943-954). The bounds are used to quantify the accuracy of negative binomial approximation to parasite counts in hosts. Since the infectivity of a population can be expected to be proportional to its total parasite burden, the Wasserstein metric is the appropriate choice.Comment: Published at http://dx.doi.org/10.3150/14-BEJ595 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

The Impact of Capital Intensive Farming in Thailand: A Computable General Equilibrium Approach

The aim of this study is to explore whether efforts to encourage producers to use agricultural machinery and equipment will significantly improve agricultural productivity, income distribution amongst social groups, as well as macroeconomic performance in Thailand. A 2000 Social Accounting Matrix (SAM) of Thailand was constructed as a data set, and then a 20 production-sector Computable General Equilibrium (CGE) model was developed for the Thai economy. The CGE model is employed to simulate the impact of capital-intensive farming on the Thai economy under two different scenarios: technological change and free trade. Four simulations were conducted. Simulation 1 increased the share parameter of capital in the agricultural sector by 5%. Simulation 2 shows a 5% increase in agricultural capital stock. A removal in import tariffs for agricultural machinery sector forms the basis for Simulation 3. The last simulation (Simulation 4) is the combination of the above three simulations. The results for each simulation are divided into four effects: input, output, income and macroeconomic effects. The results of the first two simulations produced opposite outcomes in terms of the four effects. Simulation 2 accelerated the capital intensification of all agricultural sectors, whereas Simulation 1 led to more capital intensity in some agricultural sectors. The effects of the input reallocation had a simultaneous impact on output in every sector. Simulation 1 led to a fall of almost all outputs in the agricultural sectors, whereas there was an increase in agricultural output in Simulation 2. In terms of domestic income effects, as a result of the decline of the average price of factors in Simulation 1, there was a decrease in factor incomes belonging to households and enterprises. Consequently, government revenue decreased by 0.7%. In contrast, Simulation 2 resulted in an increase in all incomes above. Finally, regarding macroeconomic variables, Simulation 1 had a negative impact on private consumption, government consumption, investment, imports and exports, resulting in Gross Domestic Product (GDP) decreasing by 0.8%. On the other hand, Simulation 2 had a positive impact on those same variables, affecting a 0.4% rise of GDP. The effects of Simulation 3 were very small in everything compared with the first two simulations. The effect of Simulation 4 was mostly dominated by Simulations 1 and 2; the negative results of Simulation 1 were compensated by the positive effects of Simulation 2.Capital intensive farming, CGE, general equilibrium, SAM, Thailand, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Productivity Analysis,

Um cenário de aprendizagem com robots para desenvolver competência estatística

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Reactive market power analysis using must-run indices

This paper investigates the issues of reactive power must-run capacity in power system operations, hence in electricity markets. A must-run index-based method is proposed in the paper to measure the market power held by reactive power suppliers. The Nordic 32-bus system and the IEEE 118-bus system are used to test the proposed method. The market power holders of reactive power found using the proposed method are in accord with that found in the realistic Nordic system operation and in the existing analysis of IEEE 118-bus system. The paper identifies through must-run indices possible conditions that could lead to market power in the case of applying a bid structure within a market framework. Furthermore, market structure drawbacks can cause the appearance of market power even in a topologically ideal system. © 2008 IEEE.published_or_final_versio