Abstract This study is based on the data from the Survey of Family Income and Expenditure by the Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The analyses performed include risks of poverty and trends, causes of poverty in working family, and sources of change in working family poverty rate. There are four findings in this study: (1) The ratios of working household members and working-age population to the total population in poverty have decreased year by year. (2) The low fertility rate and aging problems have changed the constitution of the poor, and the influence of these problems will continue to rise. (3) The working poverty rate is determined by three variables: work conditions, family conditions, and environment/system conditions. However, in recent years, human capital and family conditions have gradually lost their sensitivity as indicators to the risks of poverty. (4) The main source of the fluctuations of the working poverty rates between 1988 and 2016 is from the characteristics of family and its members, which include environment/system conditions, work conditions, and family conditions, in order of decreasing influence. As reflected in the results, although the problem of working poor is not seriousin Taiwan, the strength to alleviate household poverty through market and government revenues is still flimsy. The overall social return and redistribution system still has room for improvement in the future. Keywords: in-work poverty, causes of poverty, poverty rate

Abstract There has been a significant increase in the number of Taiwanese working abroad. This article identifies three important aspects for further investigations. First, the age group of 30 and under grew fastest as compared to other age groups. Second, a great majority of migrants working outside Taiwan are college-educated or above. Third, young migrants go to a much more diverse list of destination countries. This article presents findings based on in-depth interviews with Taiwanese young college-educated workers in China and Japan, conducted between 2015 and 2019. This article argues that the influence of access to mobility triggers people to become potential migrants by acquiring motivations, channels, and resources to facilitate migration, a process of accumulating motility. Major findings include the following. First, increasingly, young college graduates acquire aspirations to migrate abroad for career development through international exchanges opportunities provided by universities. Second, digitalized recruitment platform has become more and more diverse and available to potential migrants to utilize for realizing the migration intentions. Third,the above-mentioned mechanisms are found to be more active in linking Taiwanese young people with China and Japan. Consequently, these two countries become major magnets for attracting young workers from Taiwan. These findings could further our understanding of youth migration that has occurred in many parts of regions. Keywords: skilled migration, migration motility, youth migration, crossstrait relations, Taiwanese expatriates

Abstract Population policy is essential to national development and population projection is often used to provide insightful suggestions for planning government policies and allocating public resources. The cohort component method is currently used in projecting the national level population in Taiwan, but this method requires detailed population data, such as the records of births, deaths, and migration. It is difficult to acquire these data in county and township levels and we need to seek an alternative method for the subnational population projection. In this study, we evaluate whether the cohort change ratio (CCR), proposed by Hamilton-Perry method, is suitable for the subnational population projection via backcasting the historical data in Taiwan (1975-2019). In specific, we are interested in comparing the projecting accuracy of CCR and cohort component methods, and we found that the CCR method can be used for short-term projections (e.g., 15 years or less) for county and township levels. Also, our projection errors are smaller by using the single-age data (comparing to 5-age group data), and there are little differences in using block bootstrap or weighted average to predict the future CCR. Keywords: small area population projection, cohort change ratio, simulation, backcast, migration