Earticle

The results of the empirical analysis showed that ‘economic factors’ were the most important influencing factors on the ‘residential satisfaction’ of purchased rental housing tenants. Next, ‘external housing factors’, ‘management factors’, and ‘location factors’ were analyzed to have a significant impact on ‘residential satisfaction’. However, ‘social factors’ and ‘internal housing factors’ were found to be insignificant. The policy implications are as follows: The most important variable is ‘economic factors’, which means that it is urgent for the government to provide support policies for purchased rental housing tenants who have become more burdened with housing costs due to the aftermath of COVID-19 and the recent global triple-dip recession. In addition, the importance of ‘external housing factors’ and ‘location factors’ suggests a change in the existing housing purchase process for business owners to more actively develop indicators that improve the quality of life of tenants. Finally, the importance of the “management factors” suggests that owners of new purchased rental housing also need to establish a management system to proactively respond to housing deterioration.

본 연구는 주택가격 상승 충격이 저출산에 미치는 영향과 각 변수들의 합계출산율 변동 기여도를 추정하였다. 본 연구는 기존 연구들이 시도하지 않았던 샤플리 분해와 패널 VAR의 예측오차분산분해를 통해 과거 출산율 하락 경험치에 대한 각 변수들의 기여도와 각 변수의 향후 기여도를 추정하여 차별성이 있다. 본 연구의 주요 분석결과는 다음과 같다. 우리나라 합계출산율의 하락은 최근 합계출산율 하락 흐름에 강한 영향을 받았으며, 이 영향력은 향후 미래에도 지속될 것으로 전망되었다. 주거비의 경우는 과거 주택 매매가격은 전세가격에 비해 상대적으로 합계출산율 변동에 미친 기여도가 작았으나, 향후 미래에는 장기적으로 그 영향력이 커질 것으로 전망되었다. 주택 매매가격, 전 세가격 이외 사교육비 역시 합계출산율 하락에 주요 원인으로 작동하였음을 실증하였고, 높은 사교육비 부담이 장기 적으로도 합계출산율을 낮출 것으로 전망되었다.

This study estimated the impact of the shock of housing price increase on the total fertility rate and the contribution of each variable to changes in the TFR. This study is differentiated by estimating the contribution rate of each variable to the fertility rate through the Shapley decomposition and the panel VAR's forecast error variance decomposition, which previous studies have not attempted. The main results of this study are as follows. First, the decline in the TFR in Korea has been strongly influenced by the recent decline in the total fertility rate, and this influence is expected to continue in the future. In the case of housing costs, in the past, housing sales prices had a relatively small contribution to changes in the total fertility rate compared to the jeonse prices, but their influence is expected to increase in the long term in the future. It has been demonstrated that private education expenses other than housing sale price and Jeonse price also acted as a major cause of the decline in the total fertility rate.

Poverty is largely a rural phenomenon in sub-Saharan Africa and the key contributors to poverty are low mean per capita income and its inequitable distributions. The contribution of mean income and inequality to spatial variations in rural poverty were investigated in this study using the 2003/04 National Living Standard Survey by the National Bureau of Statistics (NBS). The data were analyzed using descriptive statistics and Shapley Decomposition (SD) techniques. Results showed that across the GPZs, the contributions of mean income to change in poverty rates were higher than inequality (Ly) for both incidence of poverty ( P0 ) and poverty gap ( P1 ). On the other hand, the contribution of mean income to change in severity of poverty ( P2 ) was higher than Ly in North-East ( μ = 0.0530; Ly = -0.0334); North-West ( μ = 0.0844; Ly = 0.0429); South-East ( μ = -0.0505; Ly = -0.0136); South- South ( μ = -0.0254; Ly = -0.0048); South-West ( μ = -0.0450; Ly = -0.0201). However, inequality contributed more than mean income in North-Central ( μ = 0.0184; Ly = 0.0240). The marginal contributions of within-GPZs inequality to poverty indices were higher than between-GPZs inequality.

As it is the poor households known to spend over 50% of their budget share on food, which is a risk of falling back into poverty as a result of food price changes. Thus, this research aims to determine aside from what factors contributed to food price and non-food price changes across countries in Latin America; how increases in food price could undermine the progress achieved in poverty reduction by assessing food and non-food expenditure of low income households of two lower-income, two upper-middle income and two higher income countries in Latin America. Using Shapley’s Value Decomposition to evaluate food expenditure to estimate each components effect (food price, non-food price and income) on aggregate poverty in Bolivia, Chile, Colombia, Ecuador, Honduras and Uruguay. When food and non-food inflation can influence the level of purchasing power and therefore each individual household’s economic means (real income) to acquire the food requirements needed to attain their optimum level of growth. We found that food and non-food consumption are more inelastic for Honduras and Uruguay, while more elastic for Ecuador and Chile. In terms of the estimated poverty impact, we found that poverty headcount rates increased in all the six economies observed, with a varying poverty condition across the six countries analyzed; the highest poverty headcount ratios have being obtained for Colombia, followed by Uruguay and Chile. Whereas, the lowest poverty headcount ratios were registered for Bolivia, Ecuador, and Honduras.

본 연구는 지니계수에 대한 샤플리 값 분해를 통해 원천별 소득이 농가소득 불평등에 기여하는 정도를 분석하고 정책적 시사점을 제시한다. 본 연구는 농가소득 중 경상소득에 초점을 맞추고 있다. 분석 자료는 통계청의 2013 ~ 2017년 농가경제조사 원자료를 이용한다. 연구결과 정부가 농가 경상소득에 대한 전체적인 불평등도를 낮추고자 할 경우, 평균 샤플리 값 분해를 통해 기여도가 높게 나타난 농업소득, 사업외소득, 겸업소득의 순으로 불평등도를 완화시켜주는 정책을, 소득원천별 불평등 기여도를 완화시키고자 할 경우 영점 샤플리 값 분해를 통해 기여도가 높게 나타난 농업소득, 사적보조금, 겸업소득 등의 불평등도를 완화시켜주는 정책을 개발하는 것이 효과적인 것으로 나타났다. 농가 경상소득의 불평등은 기본적으로 가구요인, 인구·환경·사회·경제적 요인, 정부 정책요인 등 다양한 요인들이 결합된 결과로 나타나는 것이므로 정부는 국가 전체적인 농업 및 소득 정책의 틀 속에서 원천별 소득의 불평등 문제를 완화할 수 있는 방안을 제시해야 할 것이다.

This study analyzes the degree of contribution of income sources to the income inequality among farm households through the Shapley value decomposition of the Gini coefficient and suggests policy implications. Farm Household Economy Survey raw data from 2013 to 2017 are used for the analysis. As a result of mean equalized Shapley value decomposition, it would be effective to develop a policy that alleviates inequality in order of agricultural income, non-farm business income and sideline income if the government wants to reduce overall inequality in farm household income. On the other hand, as a result of zero Shapley value decomposition, it would be effective to develop a policy that mitigates the inequality in order of agricultural income, private subsidy and sideline income if the government wants to mitigate the contribution of each income source to inequality. Inequality of farm household income is basically a combination of various factors such as household population, environment, social, economic, and government policy factors. Therefore, the government needs to design farm household income inequality mitigation policy by income source through comprehensive consideration of these factors.

본 연구에서 우리는 협조적 게임이론에서 사용되는 샤플리값(Shapley value)을 이용하여 우리나라의 소득 및 자산 불평등에 대한 원천별 한계기여를 추계한다. 샤플리값을 이용한 분해를 적용할 때 우리는 Chantreuil and Trannoy(1999)를 따라 두 가지 방법을 사용한다. 첫 번째 방법은 영점 샤플리값 분해(zero Shapley value decomposition method)로 원천별 한계기여를 계산할 때 모든 사람들에게 여타 원천들의 값으로 0을 부여한 후 각 원천별 한계기여를 계산하는 방법이다. 두 번째 방법은 평균 샤플리값 분해(mean equalized Shapley value decomposition method)로 모든 사람들에게 여타 원천들의 값으로 각각의 평균값을 부여한 후 원천별 기여를 계산하는 방법이다. 후자의 방법에서는 원천별 점유율이 중요한 역할을 하지만 전자의 방법에서는 원천별 점유율이 역할을 하지 않는다. 우리는 재정패널 7개년(2008~2014년) 자료를 사용하여 전체집단에 대해서 뿐 아니라 연령대별로도 소득 및 자산 불평등의 원천별 기여도를 분석하였다. 먼저 전체집단에 대한 분석 결과를 재정패널 2014년 기준으로 살펴보면 다음과 같다. 소득불평등에 대한 원천별 기여를 살펴보면 평균 샤플리값 분해를 이용한 경우에는 소득불평등에 대한 노동소득의 절대기여도가 80% 이상을 차지하고 자산소득의 기여도는 4.2%로 나타나 노동소득의 불평등이 전체불평등을 주도하는 것으로 나타나지만, 영점 샤플리값 분해를 이용하면 자산소득의 기여도가 약 80%를 차지하고 노동소득의 기여도는 –35.3%로 나타나 자산소득의 불평등이 전체소득불평등의 주요인이며 노동소득은 오히려 전체소득불평등을 감소시키는 요인으로 나타난다. 자산불평등에 대한 원천별 기여를 살펴보면 평균 샤플리값 분해를 이용하는 경우에는 부동산자산의 기여도 (약 80% 이상)가 금융자산의 기여도 (12%)보다 큰 것으로 나타나지만 영점 샤플리값 분해를 사용하면 금융자산의 기여도 (약 40%)가 부동산자산의 기여도(28%) 보다 큰 것으로 나타난다. 연령대별 분석 결과를 살펴보면, 연령대가 높을수록 소득 불평등도가 증가하는데, 그 주요 원인은 연령대가 높아질수록 자산소득의 불평등 기여도가 높아지기 때문이다. 자산의 경우 연령대가 높아질수록 부동산자산의 기여도가 높아지게 되는데 그 중 현 거주주택자산의 기여도가 높아진다. 반대로, 연령대가 낮을수록 전월세 보증금의 기여도가 높아진다.

Using the Shapley-value decomposition methods, we estimate the marginal contribution of each source of income and asset to the inequality of income and asset in South Korea. Following Chantreuil and Trannoy(1999), we apply two different decomposition methods when computing marginal contribution of each source to the entire inequality: the zero Shapley-value decomposition method, which assigns to all households zero values for all other sources than the source of interest, and the mean equalized Shapley-value decomposition method, which assigns mean values to all households for all other sources than the source of interest. We use the Korean Tax and Expenditure Panel Studies (2008-2014) as the dataset, and decompose inequality not only for the entire sample but also by age. Regarding income inequality, labor income is found to contribute much more to the entire inequality than asset income when we apply the mean equalized Shapley value decomposition method, while asset income is found to be much more important than labor income when we apply the zero Shapley-value decomposition method. Regarding asset inequality, real estates are found to contribute much more to the entire inequality than financial assets when we apply the mean equalized Shapley value decomposition method, while financial assets are found to contribute slightly more to the entire inequality than real estates.