• Journal of the Korean association of regional geographers
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• v.17 no.1
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• pp.75-95
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• 2011

A birth cohort approach to the Household life-cycle model could be an alternative to cross-sectional data. In this study, each residential mobilities of birth cohorts' is traced by the cohort data from repeated cross-section in the case of Jinju city. Because of the differences in fertilities by era, the volume of each cohort as a consumer in housing has varied and the condition of housing stock also has changed as the time goes by. These changes in housing make not only age effect stressed in Rossi's model, but also cohort and period effect. Due to theses effects of time, every residential mobility trajectories of generations' is different especially in earlier life stages. As households get older, it is found that the age effect reduces and the probability of residential mobility is lower. As this result, the residential succession and filtering between the earlier and latter generations is weakened and the residential segregation could be happened by birth cohort.

• The Korean Journal of Applied Statistics
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• v.28 no.4
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• pp.703-719
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• 2015

We propose an extension of the Lee and Jho (2015) mean reverting the two factor mortality model by incorporating a period-specific cohort effect. We found that the consideration of cohort effect improves the mortality fit of Korea male data above age 65. Parameters are estimated by the weighted least squares method and Metropolis algorithm. We also emphasize that the cohort effect is necessary to choose the base survival index to calculate longevity bond issue price. A key contribution of the article is the proposal and development of a method to calculate the longevity bond price to hedge the longevity risk exposed to Korea National Pension Services.

• Korea journal of population studies
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• v.35 no.1
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• pp.151-179
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• 2012

This study investigates birth cohort and educational differences in the marital and fertility life course using the Hernes model. First, lifetime marriage rates remain high across birth cohorts but men in the youngest birth cohort(1965-74) experience a somewhat significant reduction in ever-marriage rates. Second, this study also finds educational differences in lifetime marriage rates across birth cohorts. The likelihood of being never married is particularly high for poorly educated men in the youngest birth cohort but women show the opposite pattern. Third, quantum changes in the fertility transition are more likely to be the changes in higher-order births, while the changes in first and second births are mainly tempo changes. Fourth, the negative association between education and fertility is significantly larger for higher-order births. Finally, marriage and fertility show the opposite pattern in their association with education. Overall, educational differences in lifetime marriage rates become stronger across birth cohorts but the association between education and higher-order births shows the opposite pattern.

• Korea journal of population studies
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• v.29 no.2
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• pp.53-88
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• 2006

The major aim of this paper is to develop a hypothetical set of age-specific fertility rates which are logically derived and reasonably accurate in the projection of future population. The first procedure is to select a generalized log-gamma distribution model, which includes Coale-McNeil nuptiality model, in order to estimate and project a set of age-specific fertility rates by birth cohort and birth order. The second is to apply the log-gamma model with an empirical adjustment to the actual data to estimate and project the future fertility rates for relatively young birth cohorts who did not complete their reproductive career. This study reconstructs or translates a set of cohort age-specific fertility rates into a set of period age-specific fertility rates which must be hypothesized in order to establish the broader framework of future population projection. For example, the fertility at age 20 in the year of 2020 is the fertility at age 20 for the cohort born in 1990, while the fertility at age 21 in the year of 2020 is the fertility at 21 for the cohort born in 1989. In turn, once a set of age-specific fertility rates for the cohorts who were born up to the year of 2010, it is possible for one to establish an hypothetical set of period age-specific fertility rates which will be needed to project the future population until the year of 2055. The difference in the hypothetical system of age-specific fertility rates between this study and the 2005 special population projection comes from the fact that the fertility estimation/projection model used in this study was skillfully exploited to reflect better actual trend of fertility decline caused by rise in marriage age and increasing proportion of those who remain single until their end of reproduction. In this regard, this paper argues that the set of age-specific fertility rates derived from this study is more logical and reasonably accurate than the set of those used for the 2005 special projection. In the population projection, however, the fundamental issue of the hypothetical setting of age-specific fertility rates in relation to the fertility estimation/projection model is about how skillfully one can handle the period effects. It is not easy for one to completely cope with the problem of period effects except for the a minor period adjustment based on recent actual data, along with the given framework of a cohort-based fertility estimation/projection model.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1019-1032
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• 2013

The accurate prediction of future mortality is an important issue due to recent rapid increases in life expectancy. An accurate estimation and prediction of mortality is important to future welfare policies. The optimal selection of a mortality model is important to estimate and predict mortality; however, the period of time series data used is also an important issue. It is essential to understand that the time series data for mortality is short in Korea and the data before 1982 is incomplete. This paper divides the time series of Korean mortality into two sets to compare the parameter estimates of the LC model and LC model with a cohort effect by the period of data used. A modeling and prediction of the mortality index and cohort effect index as well as the evaluation of future life expectancy is conducted. Finally, some suggestions are proposed for the future prediction of mortality.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.335-342
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• 2015

Joint hierarchical generalized linear models proposed by Molas et al. (2013) extend the simple longitudinal model into multiple models fitted jointly. It can easily handle the correlation of multivariate longitudinal data. In this paper, we apply this method to analyze KoGES cohort dataset. Fixed unknown parameters, random effects and variance components are estimated based on a standard framework of h-likelihood theory. Furthermore, based on the conditional Akaike information criterion the correlated covariance structure of random-effect model is selected rather than an independent structure.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.347-373
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• 2021

Over the past 50 years, explorative research on the nation's mortality decline patterns has showed a decrease in age-specific mortality rates in all age groups, but there were different improvement patterns in specific mortality rates depending on ages and periods. Greater distinct improvement was observed in mortality rates among women than men, and there was a noticeable improvement in mortality rates in certain groups especially in the more recent decades, revealing a structural change in the overall trends regarding death periods. In this paper, we compare various stochastic mortality models considering cohort effects for mortality projection using Korean female mortality data and further explore the uncertainty related to projection. It also created age-specific mortality rates and life expectancy for women until 2067 based on the results of the analysis, and compared them with future age-specific mortality rates and life expectancy provided by the national statistical office (KOISIS). The best optimal model could vary depending on data usage periods. however, considering the overall fit and predictability, the PLAT model would be regarded to have appropriate predictability in terms of the mortality rates of women in South Korea.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.427-446
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• 2018

Korea will have a super-aged society within only 30 years according to the United Nations' definition of an aging society and the statistics on Korea's Population projections (2016), indicates that Korea has the fastest ageing speed in the world. There is a lack of data on long-term time-series data on death as related to pension and welfare policies compared to the rapid rate of aging. This paper estimates life expectancy over 245 years (from 1955 to 2200) through past and future forecasts as well as compares the expected life expectancy of the synthetic cohort and the real cohort. In addition, an international comparisons were made to understand the level of aging in Korea. Estimates of the back-projection period were compared with previous studies and the LC model to improve accuracy and objectivity. In addition, the predictions after 2016 reflected the declined mortality rate effect of Korea using the LC-ER model. The results showed an increase in life expectancy of about 30 years over 60 years (1955-2015) with an expected life expectancy of the real cohort over the second century (1955-2155) higher than the synthetic cohort. The comparative advantage of life expectancy of real cohorts was confirmed to be a common trend among comparative countries. In addition, Japan and Korea have a higher life expectancy and starting from 85 to 90 years old, all comparative countries show that the growth rate for the life expectancy of synthetic and real cohorts is less than previous years.

• Korea journal of population studies
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• v.32 no.1
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• pp.1-23
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• 2009

This paper uses a survey data to analyze the age-specific fertility rates, age-specific cumulative fertility rates, and ages of marriage of the five birth cohorts of Korean women born in the 1940s and thereafter. It was found that later cohorts reach their highest age-specific fertility rate at higher ages than earlier cohorts. The age-specific cumulative fertility rates of the 1950s and 1960 cohorts were found to be much lower than those of the immediately preceding cohorts, while those of the 1970s and 1980s cohorts were not different from those of the 1960s cohorts. Women belonging to later cohorts were found to get married at relatively higher ages. The estimation results of the hazard model show that women belonging to later cohorts and those with more schooling have a tendency to get married at higher ages. The effect of the birth cohorts is thought to be due to the economic, social, and cultural changes in Korea during the late 50 years or so. The time interval between a woman‘s marriage and first birth was found not to be affected by either the year of marriage or that of her birth. Also, those who remained employed for some time around their marriage and those with low schooling were found to have a lower first child birth hazard, which implies that married women’s employment status and family income play an important role in their decisions on childbirth.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.2
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• pp.166-181
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• 2020

This paper attempts to compare and analyze the intensity, trend, and regional gap of income inequality, capitalizing upon the Age-Period-Cohort model which considers age, time and cohort effects, with the 1998-2018 Korea Labor Panel (KLIPS) survey data for respondents living in the Capital and Non-Capital Regions. The main analysis results are as follows. First, in the case of both cohort and age effects, those in their 50~60s, including the so-called baby boomers and '386 generation' living in the Capital Region, have relatively lower income inequality effect compared to that of other age groups and cohorts in the Non-Capital Region. Second, the micro-individual characteristics cannot be ignored to account for a regional gap in income inequality, but rather the effects of structural and institutional omitted variables and the social discrimination effects of individual characteristics variables are more significant in explaining it. Overall, intra-and inter-cohort income inequalities appear to overlap.