{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T18:10:52Z","timestamp":1784139052910,"version":"3.55.0"},"reference-count":35,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,2,18]],"date-time":"2020-02-18T00:00:00Z","timestamp":1581984000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Hong Kong Government","award":["SPPR-12"],"award-info":[{"award-number":["SPPR-12"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Providing social security to the population in need has become a major expenditure for many governments. Reducing the number of dependents in the social security system and maintaining a dynamic economically active population is a high priority concern for policymakers. A good understanding of the dynamics of the social security system\u2014specifically, who enters and who exits the system\u2014would be helpful for formulating effective interventions. Here, we made use of the data of Hong Kong\u2019s Comprehensive Social Security Assistance (CSSA), which is currently a basic welfare scheme in Hong Kong that provides supplementary payments to households that cannot support themselves financially. We proposed a stochastic model to examine the in- and out- movement in the CSSA scheme and conducted elasticity analyses. The elasticity analyses allowed us to identify the potential target groups of people that would lead to the largest reduction in the number of the CSSA recipients in the system. This analytical method can also reveal whether policies would be more effective in preventing people from entering the CSSA system or helping them leave the CSSA scheme. Our analyses suggest that targeting those aged 30\u201349 with children would have the largest impact. Additionally, we found that policies that aim to prevent this group from entering the CSSA system would be more effective in reducing the number of CSSA recipients compared with policies that aim to help them exit. In contrast, for the younger age group of 10\u201329, policies that help them leave CSSA would be more effective than policies that prevent them from entering CSSA. Providing employment for those unemployed in this younger group would be more effective. The results indicate that by tailoring measures to specific subgroups, the overall number of CSSA recipients would be reduced, thereby improving the efficiency of Hong Kong\u2019s social security system, which has accounted for more than 16.5% of Hong Kong government expenditure in 2018, amounting to more than HKD 92 billion.<\/jats:p>","DOI":"10.3390\/ijerph17041305","type":"journal-article","created":{"date-parts":[[2020,2,19]],"date-time":"2020-02-19T04:06:01Z","timestamp":1582085161000},"page":"1305","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Optimal Strategies for Reducing Number of People in the Social Security System"],"prefix":"10.3390","volume":"17","author":[{"given":"Paul","family":"Yip","sequence":"first","affiliation":[{"name":"Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengni","family":"Chen","sequence":"additional","affiliation":[{"name":"Centre for Demographic Research, Catholic University of Louvain, 1348 Louvain-la-Neuve, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2422-305X","authenticated-orcid":false,"given":"Bing Kwan","family":"So","sequence":"additional","affiliation":[{"name":"Mathematics Department, Jilin University, Changchun 130012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwok Fai","family":"Lam","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kam Pui","family":"Wat","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,18]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2016). 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