The demographic transition in the Korean peninsula, 1910-1990: South and North Korea compared

North and South Korea have both experienced demographic transition and fertility and mortality declines. The fertility declines came later in North Korea. In 1990, the population was 43.4 million in South Korea and 21.4 million in North Korea and the age and sex compositions were similar. This evolution of population structure occurred despite differences in political systems and fertility determinants. Differences were in the fertility rate and the rate of natural increase. The total fertility rate was 2.5 children in North Korea and 1.6 in South Korea. The rate of natural increase was 18.5 per 1000 in North Korea and 9.8 in South Korea. Until 1910, the Korean peninsula was in the traditional stage characterized by high fertility and mortality. The early transitional stage came during 1910-45 under the Japanese annexation. Health and medical facilities improved and the crude birth rate rose and then declined. With the exception of the war years, population expanded as a function of births, deaths, and international migration. Poor economic conditions in rural areas acted as a push factor for south-directed migration, migration to Japan, and urban migration. Next came the chaotic stage, during 1945-60. South Korean population expanded during this period of political unrest. Repatriation and refugee migration constituted a large proportion of the population increase. Although the war brought high mortality, new medicine and disease treatment reduced the mortality rate after the war. By 1955-60, the crude death rate was 16.1 per 1000 in South Korea. The crude birth rate remained high at 42 per 1000 between 1950-55. The postwar period was characterized by the baby boom and higher fertility than the pre-war period of 1925-45. Total fertility was 6.3 by 1955-60. The late transitional stage occurred during 1960-85 with reduced fertility and continued mortality decline. By 1980-85, total fertility was 2.3 in the closed population. The restabilization stage occurred during 1985-90, and fertility declined to 1.6. In North Korea, strong population control policies precipitated fertility decline. In South Korea, the determinants were contraception, rising marriage age, and increased use of abortion concomitant with improved socioeconomic conditions.     

A Bayesian multiple structural change regression model with autocorrelated errors

This paper develops a new Bayesian approach to change-point modeling that allows the number of change-points in the observed autocorrelated times series to be unknown. The model we develop assumes that the number of change-points have a truncated Poisson distribution. A genetic algorithm is used to estimate a change-point model, which allows for structural changes with autocorrelated errors. We focus considerable attention on the construction of autocorrelated structure for each regime and for the parameters that characterize each regime. Our techniques are found to work well in the simulation with a few change-points. An empirical analysis is provided involving the annual flow of the Nile River and the monthly total energy production in South Korea to lead good estimates for structural change-points.     

Complex demoeconomic dynamics

We show how various kinds of qualitative long run demoeconomic behavior depend on household preferences, productivity and the cost of childrearing. In particular, a dominant trend in growth can be interspersed with periods of fluctuation as slowly moving changes in productivity, preference and child care costs push nonlinearities past crucial bifurcation points. Moreover, nonperiodic, essentially unpredictable demoeconomic behavior is robust, thus suggesting a possible explanation for persistent and substantial errors in population forecasts.[/p]A partial draft of the present paper was first presented at the annual meetings of the Population Association of America, San Francisco, April 3, 1986. The computer experiments were performed by Changseob Kim and Weihong Huang.     

An outcome evaluation of refusal skills program as a drug abuse prevention strategy

In recent years successful strategies developed in the antismoking campaign became the basis for widely publicized and federally endorsed antidrug "Just Say No" programs. Similarly, many refusal skills programs have been introduced as a new strategy in adolescent drug abuse prevention. However, none of these programs have been evaluated. While employing a typical refusal skills program entitled "WHOA! A Great Way To Say NO," the effectiveness of the program was examined. Through this outcome evaluation, it has been learned that the program was not able to impact on the "high-risk" attitudinal syndromes that are closely related to student drug involvement. Unexpectedly, a significantly larger proportion of students in the program felt it was more difficult to say "No" at the time of the posttest than during the time of the pretest. This seems to suggest that the program participants became more attentive to the issues surrounding saying "No" or, perhaps, were more sensitized to the whole issue involving saying "No," thereby making it more difficult for them to say "No" during the posttest period.     

An extended proportional hazards model for interval-censored data subject to instantaneous failures

Lifetime Data Analysis - The proportional hazards (PH) model is arguably one of the most popular models used to analyze time to event data arising from clinical trials and longitudinal studies. In...     

Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework

Predictive mean matching imputation is popular for handling item nonresponse in survey sampling. In this article, we study the asymptotic properties of the predictive mean matching estimator for finite-population inference using a superpopulation model framework. We also clarify conditions for its robustness. For variance estimation, the conventional bootstrap inference is invalid for matching estimators with a fixed number of matches due to the nonsmoothness nature of the matching estimator. We propose a new replication variance estimator, which is asymptotically valid. The key strategy is to construct replicates directly based on the linear terms of the martingale representation for the matching estimator, instead of individual records of variables. Simulation studies confirm that the proposed method provides valid inference.     

An exploration of mental health literacy among African American clergy

The purpose of this qualitative study was to explore African American clergy's mental health literacy with older congregants 60 years of age and older. Using a grounded theory approach, we recruited a purposive sample of 9 African American clergy representing diverse ages, denominations, locales, and educational levels. Data was coded and classified according to Kevin's (1976) typology of pastoral counseling and Jorm et al.'s (1997) conceptual model of mental health literacy. Findings from data analysis revealed study respondents were adherents of Kevin's Religious-Community (R-C) model. Additionally, the following themes emerged: loss of cognitive functioning, psychosocial stressors, religiosity, and appreciation for professional assistance, cultural barriers, and key informants/familiarity with formal mental health providers which partially maps onto Jorm et al.'s conceptual model of mental health literacy.     

Bayesian variable selection for the Cox regression model with missing covariates

In this paper, we develop Bayesian methodology and computational algorithms for variable subset selection in Cox proportional hazards models with missing covariate data. A new joint semi-conjugate prior for the piecewise exponential model is proposed in the presence of missing covariates and its properties are examined. The covariates are assumed to be missing at random (MAR). Under this new prior, a version of the Deviance Information Criterion (DIC) is proposed for Bayesian variable subset selection in the presence of missing covariates. Monte Carlo methods are developed for computing the DICs for all possible subset models in the model space. A Bone Marrow Transplant (BMT) dataset is used to illustrate the proposed methodology.     

How does economic globalisation affect the welfare state? Focusing on the mediating effect of welfare regimes

In recent years the impact of globalisation on the welfare state has become a major issue in comparative policy studies. Some empirical studies demonstrate a negative relationship between globalisation and the welfare state, while others show adverse findings or a non-significant relationship. The impact of globalisation, however, can be neither uniform nor unidirectional because of the differences in the political economies of individual welfare states. Welfare regimes reflect qualitative differences in arrangements of welfare institutions and the associated enduring configuration of the welfare nexus, suggesting that welfare regimes may influence the impact of globalisation on the welfare state. We scrutinise the relationship between globalisation and the welfare state by sampling 18 affluent countries from 1980 to 2001 and concentrating on the mediating effect of three welfare regime types. Our study provides a comprehensive examination of the relationship between globalisation and the welfare state using a state-of-the-art analytical technique – the mixed-effect model. Findings suggest that welfare regimes respond differently to the impact of globalisation and therefore mediate the relationship between globalisation and the welfare state. Globalisation negatively affects the welfare state in a social democratic regime, while it marginally affects the welfare state in liberal and conservative regimes.