• 토지주택연구
• /
• 제2권4호
• /
• pp.345-353
• /
• 2011

This paper is focused on the sustainability of public rental housing policy. We have analyzed the general fiscal conditions of central government, the public welfare fiscal conditions, the public expenditure on rental housing, and the Korea Land & Housing Corporation (LH) financial structure. Central government fiscal conditions is controlled by the midium-term fiscal operation plan(2010~2014) and fiscal rules. And the fiscal mandatory expenditures on welfare is increased rapidly by the expansion of beneficiaries, but the fiscal discretionary expenditures particularly on public rental housing can be gradually cut down. LH, the dominant agency responsible for affordable housing, is now confronted with financial distress accruing to excessive burden for public rental housing construction. As a result this paper, we find the discrepancy between the fiscal conditons and public rental housing policies. We suggest the fiscally sustainable rental housing policy. Firstly, the construction plan should be realized reflecting the market and fiscal conditions. Secondly, the provsion and financing system of rental housing should be rebuild within the government fiscal condtions and financial ability of LH.

• 사회복지연구
• /
• 제49권3호
• /
• pp.35-60
• /
• 2018

본 연구는 탈산업사회를 경험한 복지국가들이 중앙정부의 재정 압박과 새로운 사회적 위험에 대해 지방정부 책임과 역할의 확대를 포함한 지방분권을 그 대응방안으로 삼았다는 점을 주목하여, 재정분권이 복지재정에 미친 영향을 파악하고자 하였다. 이는 복지재정의 다면적 특성에 따라, 재정분권이 복지지출에 미친 영향과 현물급여 비중에 미친 영향을 파악하는 것으로 구체화되었다. OECD 19개 회원국의 1997년에서 2013년까지의 시기를 대상으로 한 결합시계열회귀분석 분석결과는 다음과 같다. 첫째, 재정분권 수준이 증가할수록 국가의 복지지출 수준은 감소하는 것으로 나타났다. 둘째, 재정분권 수준이 증가할수록 전체 복지지출 중 현물급여의 지출이 증가하는 것으로 파악된다.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권1호
• /
• pp.665-673
• /
• 2021

Default has become an extreme concern in the current world due to the financial crisis. The previous prediction of companies' bankruptcy exhibits evidence of decision assistance for financial and regulatory bodies. Notwithstanding numerous advanced approaches, this area of study is not outmoded and requires additional research. The purpose of this research is to find the best classifier to detect a company's default risk and bankruptcy. This study used secondary data from the Pakistan Stock Exchange (PSX) and it is time-series data to examine the impact on the determinants. This research examined several different classifiers as per their competence to properly categorize default and non-default Pakistani companies listed on the PSX. Additionally, PSX has remained consistent for some years in terms of growth and has provided benefits to its stockholders. This paper utilizes machine learning techniques to predict financial distress in companies listed on the PSX. Our results indicate that most multi-stage mixture of classifiers provided noteworthy developments over the individual classifiers. This means that firms will have to work on the financial variables such as liquidity and profitability to not fall into the category of liquidation. Moreover, Adaptive Boosting (Adaboost) provides a significant boost in the performance of each classifier.