Ethnic minority development in Vietnam : a socioeconomic perspective

The authors examine the latest quantitative evidence on disparities in living standards between and among different ethnic groups in Vietnam. Using data from the 1998 Vietnam Living Standards Survey and 1999 Census, they show that Kinh and Hoa ("majority") households have substantially higher living standards than"minority"households from Vietnam's other 52 ethnic groups. Subdividing the population into five broad categories, the authors find that while the Kinh, Hoa, Khmer, and Northern Highland minorities have benefited from economic growth in the 1990s, the growth of Central Highland minorities has stagnated. Disaggregating further, they find that the same ethnic groups whose living standards have risen fastest are those that have the highest school enrollment rates, are most likely to intermarry with Kinh partners, and are the least likely to practice a religion. The authors then estimate and decompose a set of expenditure regressions which show that even if minority households had the same endowments as Kinh households, this would close no more than a third of the gap in per capita expenditures. While some ethnic minorities seem to be doing well with a strategy of assimilating (both culturally and economically) with the Kinh-Hoa majority, other groups are attempting to integrate economically while retaining distinct cultural identities. A third group comprising the Central Highland minorities, including the Hmong, is largely being left behind by the growth process. Such diversity in the socioeconomic development experiences of the different ethnic minorities indicates the need for similar diversity in the policy interventions that are designed to assist them.Anthropology,Primary Education,Social Inclusion&Institutions,Health Monitoring&Evaluation,Public Health Promotion,Primary Education,Health Monitoring&Evaluation,Anthropology,Poverty Assessment,Gender and Education

Shifts in Living Standards: The Case of Vietnamese Households 1992-1998

This paper investigates determinants of shifts in living standards for Vietnamese households, measured by the difference in consumption at two different points in time. In agreement with studies on other countries, results show that education, household composition, and community infrastructure are strongly related to consumption changes. A main contribution of the paper is to propose novel analytical techniques for the modeling of shifts in living standards. In particular, it proposes the use of Directed Acyclic Graphs to help identify direct and indirect predictors of consumption differences and protect against spurious correlations, and advocates the use of Multivariate Adaptive Regression Splines (MARS) to help identify nonlinearity and interactions. It suggests graphical methods to guide the interpretation of the models.Vietnamese households, living standards, shifts in living standards, household vulnerability, household consumption

Shifts in Living Standards: The Case of Vietnamese Households 1992-1998

This paper investigates determinants of shifts in living standards for Vietnamese households, measured by the difference in consumption at two different points in time. In agreement with studies on other countries, results show that education, household composition, and community infrastructure are strongly related to consumption changes. A main contribution of the paper is to propose novel analytical techniques for the modeling of shifts in living standards. In particular, it proposes the use of Directed Acyclic Graphs to help identify direct and indirect predictors of consumption differences and protect against spurious correlations, and advocates the use of Multivariate Adaptive Regression Splines (MARS) to help identify nonlinearity and interactions. It suggests graphical methods to guide the interpretation of the models.Vietnamese households, living standards, shifts in living standards, household vulnerability, household consumption

Bayesian Analysis Of Poverty Rates: The Case Of Vietnamese Provinces

This paper presents a Bayesian analysis of poverty rates in urban Ho Chi Minh City and rural Nghe An province in Vietnam. Using mixtures of beta distributions as priors for the poverty rates, we find that, when the prior is reasonably informative, our approach yields more accurate estimated poverty rates than a frequentist approach. On the other hand, we find that, in the presence of poor/non-poor misclassification, average probabilities of posterior credible intervals for poverty rates can fall well short of .95 even with sample sizes such as 2000 or 3000 when the width of the interval is for example four percentage points. In general, we suggest reporting prior and posterior means and standard deviations along with traditional frequentist measures. Our results rely on techniques due to Nandram and Sedransk (1993) and Rahme, Joseph and Gyorkos (2000), and make use of the software WINBUGS

Imputing unknown competitor marketing activity with a Hidden Markov Chain

We demonstrate on a case study with two competing products at a bank how one can use a Hidden Markov Chain (HMC) to estimate missing information on a competitor's marketing activity. The idea is that given time series with sales volumes for products A and B and marketing expenditures for product A, as well as suitable predictors of sales for products A and B, we can infer at each point in time whether it is likely or not that marketing activities took place for product B. The method is successful in identifying the presence or absence of marketing activity for product B about 84% of the time. We allude to the issue of whether, if one can infer marketing activity about product B from knowledge of marketing activity for product A and of sales volumes of both products, the reverse might be possible and one might be able to impute marketing activity for product A from knowledge of that of product B. This leads to a concept of symmetric imputation of competing marketing activity. The exposition in this paper aims to be accessible and relevant to practitioners

Introduction to Data Analytics and Data Mining for Social Media Minitrack

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Virtual piano instruction for the college learner

This article investigates the affordability and feasibility of conducting virtual piano lessons for the college level learner. It proposes an approach that works well and requires equipment costing approximately $300 per student. We outline the pros and cons of conducting virtual piano lessons online. The main benefit is overcoming geographical distances, whereas limitations include challenges such as the instructor being able to check issues such as fingerings or dynamics. Latency is not a major problem as long as only one person is playing at any given time, as found in past work. The process of teaching and learning online requires the student to be strongly motivated, and it is helpful for instructor and student to have worked together before in non-virtual environments

Data Mining CEO Compensation

The need to pre-specify expected interactions between variables is an issue in multiple regression. Theoretical and practical considerations make it impossible to pre-specify all possible interactions. The functional form of the dependent variable on the predictors is unknown in many cases. Two ways are described in which the data mining technique Multivariate Adaptive Regression Splines (MARS) can be utilized: first, to obtain possible improvements in model specification, and second, to test for the robustness of findings from a regression analysis. An empirical illustration is provided to show how MARS can be used for both purposes

Optimization of the marketing mix in the health care industry

This paper proposes data mining techniques to model the return on investment from various types of promotional spending to market a drug and then uses the model to draw conclusions on how the pharmaceutical industry might go about allocating marketing expenditures in a more efficient manner, potentially reducing costs to the consume