Bayesian analysis of time series Poisson data

This paper provides a practical simulation-based Bayesian analysis of parameter-driven models for time series Poisson data with the AR(1) latent process. The posterior distribution is simulated by a Gibbs sampling algorithm. Full conditional posterior distributions of unknown variables in the model are given in convenient forms for the Gibbs sampling algorithm. The case with missing observations is also discussed. The methods are applied to real polio data from 1970 to 1983.     

On second-order improved estimation of a gamma scale parameter

This paper concludes our comprehensive study on point estimation of model parameters of a gamma distribution from a second-order decision theoretic point of view. It should be noted that efficient estimation of gamma model parameters for samples ‘not large’ is a challenging task since the exact sampling distributions of the maximum likelihood estimators and its variants are not known. Estimation of a gamma scale parameter has received less attention from the earlier researchers compared to shape parameter estimation. What we have observed here is that improved estimation of the shape parameter does not necessarily lead to improved scale estimation if a natural moment condition (which is also the maximum likelihood restriction) is satisfied. Therefore, this work deals with the gamma scale parameter estimation as a separate new problem, not as a by-product of the shape parameter estimation, and studies several estimators in terms of second-order risk.     

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.     

Research-based service-learning: outcomes of a social policy course

Previous research has found service-learning in undergraduate social policy courses to increase students’ knowledge, skills, values, and competence. The present study utilized a sample of 60 graduate-level social work students who participated in a research-based service-learning (RBSL) project that involved collecting and analyzing data about the extent of payday loan use among bankruptcy filers and reporting results to community partners. Quantitative findings revealed significant increases in students’ personal social responsibility. Qualitative findings shed light on growth in personal social responsibility, civic awareness, policy advocacy, and personal values. Suggestions for future studies using RBSL pedagogy to teach social policy are discussed.     

Accounting for Uncertainty in Heteroscedasticity in Nonlinear Regression

Toxicologists and pharmacologists often describe toxicity of a chemical using parameters of a nonlinear regression model. Thus estimation of parameters of a nonlinear regression model is an important problem. The estimates of the parameters and their uncertainty estimates depend upon the underlying error variance structure in the model. Typically, a priori the researcher would not know if the error variances are homoscedastic (i.e., constant across dose) or if they are heteroscedastic (i.e., the variance is a function of dose). Motivated by this concern, in this paper we introduce an estimation procedure based on preliminary test which selects an appropriate estimation procedure accounting for the underlying error variance structure. Since outliers and influential observations are common in toxicological data, the proposed methodology uses M-estimators. The asymptotic properties of the preliminary test estimator are investigated; in particular its asymptotic covariance matrix is derived. The performance of the proposed estimator is compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using a data set obtained from the National Toxicology Program.     

“It’s not just talk”: ideas,discourse, and the prospects for transformational change in a homogenous nation-state

ABSTRACT

Despite decades of large-scale immigration, systemic and institutionalized racism and ethnonationalism remain very strong in South Korea. One reason is obvious: South Korea is the quintessential homogeneous nation-state. Many observers, in fact, believe that it is one of the few societies in the world that is naturally homogenous. For this and other reasons, the prospect that South Korea can or will transform from homogenous nation-state to multicultural society is generally given very short shrift. I argue, however, that small but extremely significant steps toward a multicultural society have already been made and that the key reason is due to the introduction of ‘multiculturalism’ as an idea and discourse in Korean society. While a focus on ideas/discourse is hardly new, this paper contends that it has been seriously underappreciated, particularly in analyses of South Korea, as a cause of institutional stability on the one hand, and of institutional change and transformation, on the other hand.     

The spatial dimension of human capital segregation: An empirical investigation for Seoul, Korea

This research note examines changes in the spatial patterns of human capital segregation in Seoul, Korea from 1995 to 2005, and investigates whether spatial clusters of human capital can be isolated across neighborhoods in the metropolitan area. The major finding is that the proportion of college-educated individuals in the population aged 25 years and over increased significantly over the 1995–2005 period, and human capital segregation declined. However, the spatial distribution of human capital is by nature clustered and tends to be more clustered over the period. The neighborhoods with relatively high level of human capital tend to be localized close to other neighboring areas with high level of human capital. Most of these neighborhoods are located in the southern parts of Seoul, and these spatial clusters, which can be considered as hot spots of human capital, persist throughout the period. These results may have important implications for how the spatial dimension of human capital segregation contributes to the manner through which neighborhood effects of human capital impact metropolitan socioeconomic outcomes.