The information society in Latin America and the Caribbean: development of technology and technologies for development. Abridged document

Includes bibliography

Chinese foreign direct investment in Latin America and the Caribbean: China-Latin America cross-council taskforce. Working document

Although Chinese corporations were relatively unknown in Latin America until a few years ago, their direct investments in the region have averaged about US$10 billion per year since 2010. Their presence and economic leverage have become very significant in many industries and countries of the region, but their motivation, strategy and procedures are not always well understood by Latin America’s governments, businesses and civil society. Similarly, Chinese companies still need to gain a better understanding of Latin America’s business environment and opportunities. This working document is an input for discussing the future of Chinese foreign direct investment (FDI) in Latin America at the China - Latin America cross-council taskforce at the Summit on the Global Agenda, to be held under the auspices of the World Economic Forum (WEF), in Abu Dhabi on 18-20 November 2013. It was prepared jointly by Taotao Chen, Professor of Finance of the School of Economics and Management of Tsinghua University in China and member of the WEF Global Agenda Council on China, and by Miguel Pérez Ludeña, Economic Affairs Officer at the Economic Commission for Latin America and the Caribbean (ECLAC), under the supervision of Alicia Bárcena, Executive Secretary of ECLAC and Vice-Chair of the WEF Global Agenda Council on Latin America.

Formulating bankable aid for trade projects: Guidance document

Includes bibliography.

Preliminary document of the regional instrument on access to information, participation and justice on environmental matters in Latin America and the Caribbean

This technical document has been prepared by the Economic Commission for Latin America and the Caribbean (ECLAC) as requested by the countries signatory to the Declaration on the application of Principle 10 of the Rio Declaration on Environment and Development in Latin America and the Caribbean in the Santiago Decision adopted at the fourth meeting of the focal points appointed by the Governments of the signatory countries of the Declaration held in Santiago, Chile, from 4 to 6 November 2014.

Establishing erosion susceptibility: analytical hierarchical process and traditional approaches

This study evaluated alternatives for producing erosion susceptibility maps, considering different weight combinations for an environment's attributes, according to four different points of views. The attributes considered were landform, steepness, soils, rocks and land occupation. Considered alternatives were: (1) equal weights, more traditional approach, (2) different weights, according to a previous study in the area, (3) different weights, based on other works in the literature, and (4) different weights based on the analytical hierarchical process. The area studied included the Prosa Basin located in Campo Grande-Mato Grosso do Sul State, Brazil. The results showed that the assessed alternatives can be used together or in different stages of studies aiming at urban planning and decision-making on the interventions to be applied.

O papel da comunicação no processo de transferência de tecnologia da Embrapa para a comunidade indígena Campo Alegre de Boa Vista, RR

Pós-graduação em Comunicação - FAAC

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Mating system parameters at hierarchical levels of fruits, individuals and populations in the Brazilian insect-pollinated tropical tree, Tabebuia roseo-alba (Bignoniaceae)

For many tree species, mating system analyses have indicated potential variations in the selfing rate and paternity correlation among fruits within individuals, among individuals within populations, among populations, and from one flowering event to another. In this study, we used eight microsatellite markers to investigate mating systems at two hierarchical levels (fruits within individuals and individuals within populations) for the insect pollinated Neotropical tree Tabebuia roseo-alba. We found that T. roseo-alba has a mixed mating system with predominantly outcrossed mating. The outcrossing rates at the population level were similar across two T. roseo-alba populations; however, the rates varied considerably among individuals within populations. The correlated paternity results at different hierarchical levels showed that there is a high probability of shared paternal parentage when comparing seeds within fruits and among fruits within plants and full-sibs occur in much higher proportion within fruits than among fruits. Significant levels of fixation index were found in both populations and biparental inbreeding is believed to be the main cause of the observed inbreeding. The number of pollen donors contributing to mating was low. Furthermore, open-pollinated seeds varied according to relatedness, including half-sibs, full-sibs, self-sibs and self- half-sibs. In both populations, the effective population size within a family (seed-tree and its offspring) was lower than expected for panmictic populations. Thus, seeds for ex situ conservation genetics, progeny tests and reforestation must be collected from a large number of seed-trees to guarantee an adequate effective population in the sample.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.