Examining the technical efficiency of rice producers in Bangladesh

Despite record national output in the early years of this decade there is widespread concern that rice yields in Bangladesh are below those attainable, and that given future population growth this may constrain achievement of food security and poverty reduction objectives. A frequent response to this problem is that farmers could close the gap between actual farm yields and potential yields identified in field trials if farmers who are technically inefficient could improve their current farming practices. This paper estimates and explains technical efficiency for a sample of rice farmers in Bangladesh employing Bayesian methods. The results provide insights into the distribution of technical efficiency and identify important influences on rice growing.

Profitability and technical efficiency of aquaculture systems in Pampanga, Philippines

We evaluate the profitability and technical efficiency of aquaculture in the Philippines. Farm-level data are used to compare two production systems corresponding to the intensive monoculture of tilapia in freshwater ponds and the extensive polyculture of shrimps and fish in brackish water ponds. Both activities are very lucrative, with brackish water aquaculture achieving the higher level of profit per farm. Stochastic frontier production functions reveal that technical efficiency is low in brackish water aquaculture, with a mean of 53%, explained primarily by the operator's experience and by the frequency of his visits to the farm. In freshwater aquaculture, the farms achieve a mean efficiency level of 83%. The results suggest that the provision of extension services to brackish water fish farms might be a cost-effective way of increasing production and productivity in that sector. By contrast, technological change will have to be the driving force of future productivity growth in freshwater aquaculture.

Application of a double bootstrap to investigation of determinants of technical efficiency of farms in Central Europe

The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.

Application of a double bootstrap to investigation of determinants of technical efficiency of farms in Central Europe

The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.

The error of representation: basic understanding

Representation error arises from the inability of the forecast model to accurately simulate the climatology of the truth. We present a rigorous framework for understanding this kind of error of representation. This framework shows that the lack of an inverse in the relationship between the true climatology (true attractor) and the forecast climatology (forecast attractor) leads to the error of representation. A new gain matrix for the data assimilation problem is derived that illustrates the proper approaches one may take to perform Bayesian data assimilation when the observations are of states on one attractor but the forecast model resides on another. This new data assimilation algorithm is the optimal scheme for the situation where the distributions on the true attractor and the forecast attractors are separately Gaussian and there exists a linear map between them. The results of this theory are illustrated in a simple Gaussian multivariate model.

Factors affecting the technical efficiency of production of the Brazilian banking system : a comparison of four statistical models in the context of data envelopment analysis

This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.

Comparison of different analysis techniques for the determination of muscle onset in individuals with patellofemoral pain syndrome

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

INCREASE OF AVERAGE ENERGY BY THE PROCESS OF MEASUREMENT

A paradox is pointed out and resolved by proving that the average energy E = [H] of a macroscopic system in thermal equilibrium must increase by the measurement of an observable A which does not commute with the Hamiltonian H. The proof follows as a corollary of a more general result, which states that under certain conditions the expectation value [C] of an observable C should increase by the measurement of another observable A, if [A, C] not-equal 0.