Philippine NGOs and Multistakeholder Partnerships: Three Case Studies

This paper discusses an emerging role for Philippine NGOs—building and maintaining intersectoral cooperation among various sectors of society to tackle key issues like agricultural development, HIV/AIDS, and agrarian reform. The three case studies elaborated in the paper show that Philippine NGOs play important intermediary and bridging functions crucial for the success of multistakeholder partnerships. NGOs are well equipped for this because of their middle-class and professional nature and because of various characteristics like autonomy, flexibility, and the ability to mobilize resources.     

An analysis of other countries’ international public relations in the U.S.

The purpose of this study was to examine the various aspects of international public relations by other countries in the U.S. Based on the Foreign Agency Registration Act (FARA) report in 2002, this study analyzed client, activity types, purpose of activity, and key U.S. partners for activity. This study found that (1) business organizations and central governments were major clients of international public relations in the U.S., (2) meeting with governmental officials and congressional leaders was the primary type of activity followed by information dissemination, and (3) economic purpose led by trade promotion was the primary motive for these activities.     

Optimal sampling for repeated binary measurements

The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling cost, a term related to prediction, and if relevant, a term related to learning about a treatment effect To this end, they use a nonparametric probability model relying on a minimal number of assumptions. They show how their assumption of partial exchangeability for the binary sequence of data allows the sampling distribution to be written as a mixture of homogeneous Markov chains of order k. The implementation follows the approach of Quintana & Müller (2004), which uses a Dirichlet process prior for the mixture.     

Learning Life Skills Through Challenging and Negative Experiences

Child and Adolescent Social Work Journal - Youth who are socially vulnerable are disproportionately confronted with culminating risk factors that impact their everyday lives. Within positive youth...     

Farmers' Contribution to Agricultural Social Capital: Evidence from Southern Spain

Social capital is the whole set of shared norms, values, attitudes, and beliefs that promote cooperation among individuals within the community and that has proved to be a key factor in explaining development processes. This article aims to provide an analytically reliable notion of social capital within the farming sector and a methodological tool for empirically measuring how social capital is accumulated at the farmer level. The theoretical framework proposed is based on the multidimensionality of the complex concept of social capital. Thus, to develop a comprehensive index for social capital, we identify three dimensions of the concept, structural, relational, and cognitive social capital, each one also comprising several subdimensions. This integrative approach permits creation of a composite indicator of the agricultural social capital accumulated at the farmer level, further identifying socioeconomic factors that influence its accumulation at that level. We empirically apply this methodological approach to farmers in Andalusia in southern Spain as a case study. This research provides an interesting starting point for informing policymakers about social capital and helping them implement the necessary programs to facilitate sustainable development in the agricultural sector.     

What Survey Data Reveal about Price and Wage Rigidity in Portugal

This paper exploits the information collected from a survey conducted on a sample of Portuguese firms to study the patterns of firms’ price and wage adjustments and the extent of nominal price and wage rigidities. The evidence shows that the frequency of price changes varies substantially across sectors and depends on the intensity of competition, the share of labor costs and firms’ price reviewing behavior. The results also suggest that the constraint imposed by the presence of downward nominal wage rigidity is less important in firms where the fraction of permanent and high‐skilled workers is lower and the share of flexible pay components is higher.     

An improved alternative estimation procedure for current population mean in presence of positively and negatively correlated auxiliary variables in two-occasion rotation patterns

Abstract

The present study confirms the influential role of a positively and a negatively correlated auxiliary variables in enhancing the precision of estimates of current population mean in two occasion rotation (successive) sampling. Exponential-type estimators of current population mean have been proposed for three different situations: (i) the information on a positively correlated auxiliary variable is readily available on both occasions (ii) the information on a negatively correlated auxiliary variable is readily available on both occasions and (iii) the information on both positively and negatively correlated auxiliary variables are readily available on both the occasions. The characteristics of the proposed estimators have been explored and their efficacious performances are compared with the natural and recent contemporary estimators. Optimum replacement strategies of the proposed estimation procedures have been formulated. Simulation and empirical studies are carried out to justify the proposition of the proposed estimators and appropriate recommendations have been put forward to the survey practitioners.     

Regression models to dependence for exceedance

Extreme Value Theory (EVT) aims to study the tails of probability distributions in order to measure and quantify extreme events of maximum and minimum. In river flow data, an extreme level of a river may be related to the level of a neighboring river that flows into it. In this type of data, it is very common for flooding of a location to have been caused by a very large flow from an affluent river that is tens or hundreds of kilometers from this location. In this sense, an interesting approach is to consider a conditional model for the estimation of a multivariate model. Inspired by this idea, we propose a Bayesian model to describe the dependence of exceedance between rivers, where we considered a conditionally independent structure. In this model, the dependence between rivers is captured by modeling the excess marginally of one river as a consequence of linear functions of the other rivers. The results showed that there is a strong and positive connection between excesses in one river caused by the excesses of the other rivers.     

A Bayesian model for multiple change point to extremes,with application to environmental and financial data

Abrupt changes often occur for environmental and financial time series. Most often, these changes are due to human intervention. Change point analysis is a statistical tool used to analyze sudden changes in observations along the time series. In this paper, we propose a Bayesian model for extreme values for environmental and economic datasets that present a typical change point behavior. The model proposed in this paper addresses the situation in which more than one change point can occur in a time series. By analyzing maxima, the distribution of each regime is a generalized extreme value distribution. In this model, the change points are unknown and considered parameters to be estimated. Simulations of extremes with two change points showed that the proposed algorithm can recover the true values of the parameters, in addition to detecting the true change points in different configurations. Also, the number of change points was a problem to be considered, and the Bayesian estimation can correctly identify the correct number of change points for each application. Environmental and financial data were analyzed and results showed the importance of considering the change point in the data and revealed that this change of regime brought about an increase in the return levels, increasing the number of floods in cities around the rivers. Stock market levels showed the necessity of a model with three different regimes.     

Does It Matter How We Assess Standard of Living? Evidence from Indian Slums Comparing Monetary and Multidimensional Approaches

As part of Sustainable Development Goals, the United Nations have set targets of upgrading slums and reducing poverty in all its dimensions by 2030. Policies towards improving the living conditions of slum-dwellers require proper assessment of their standard of living as well as understanding the associated characteristics. In this paper, using slum-level primary household survey data from three largest Indian cities, we, first, assess the standard of living of slum dwellers using both monetary and non-monetary approaches and then explore how various household and spatial characteristics are consistently or differently associated with both forms of assessments. We use standard monetary indicators, but to assess non-monetary standard of living, use a counting approach framework and justify the selection of specific indicators in the context of slums. Our analysis yields some interesting observations as some characteristics are differently associated with monetary and non-monetary living standards, which should affect policy designs in slums.