Poverty is a worldwide phenomenon that threatens basic human life. Despite the numerous improvements in society today, poverty has remained an issue that cannot be easily resolved. In fact, social development has actually aggravated poverty in some ways while also changing its characteristics. The elderly, individuals with less education, individuals with low income, and women are particularly vulnerable to poverty [1
Another worldwide phenomenon is the rapid increase in the number of female householders [3
]. However, this rise has been accompanied by the increasingly visible problem of women in poverty [4
]. Since Pearce [6
] introduced the concept of the feminization of poverty, gender has become an important variable in poverty studies [6
]. In many countries, women are excluded from the labor market; when there is no male responsible for supporting the family, these women may face challenges in terms of social insurance benefits. Factors such as weak human relations [7
], changes in family structure caused by divorce or death of a spouse [1
], sexual division in labor ideology, and labor market segmentation [8
] are often considered as factors contributing to poverty among female householders.
The many recent studies that have actively investigated the problem of poverty have commonly viewed it as a result of economic deprivation [9
]. When poverty is defined as a shortage of economic resources, the primary problem that poor women experience relates to material shortages of clothing, food, shelter, and more. However, poverty among women is also accompanied by social problems that go beyond economic resources and include, for example, social alienation. Hence, if the problem of women’s poverty is approached taking only economic resource shortages into account, it will be difficult to effectively design policies that address the various problems that poor women face. Accordingly, there is a need to consider women’s poverty from a multidimensional perspective that considers various issues in their lives, departing from the existing purely economic approach. Assuming that poverty has dimensions other than income, the multidimensional approach measures the level of welfare and welfare deficiency in various forms. As a result, policies that deal with poverty from a multidimensional perspective should be able to encompass sociocultural areas as well as simple income protection.
Some studies that have adopted a multidimensional approach have introduced the count approach [11
] to estimate a new poverty rate, taking into consideration various dimensions other than income-based poverty, or to infer the severity of poverty, enabling an integrated prediction of the degree of poverty. However, despite its advantages, this multidimensional approach fails to determine which dimensions have a greater relative impact on poverty; furthermore, as detailed dimensions are replaced by single indicator values, the knowledge of poverty that can be derived is limited. For example, some indicators in multidimensional poverty studies, such as the headcount ratio (H) and adjusted headcount ratio (M), are transformed from various dimensions into one dimension, which results in a loss of information regarding which dimensions are more serious in relative terms. Hence, to provide effective measures against poverty, more detailed information is needed about which is the most vulnerable group as well as which poverty dimensions have the greatest impact. If types of poverty can be classified based on various dimensions, the effectiveness of such measures can be substantially improved.
Accordingly, in this study, we attempted to classify women’s poverty into types using latent class analysis (LCA) and the multidimensional poverty concept to determine effective policy alternatives. LCA is a subset of structural equation modeling and is used to find groups or subtypes of data within multivariate categorical and/or continuously observed data [15
]. Our study contributes to the literature by identifying basic data that can be used to design more effective measures and policies to fight women’s poverty. The rest of the article is organized as follows: Section 2
covers the theoretical background for this study while Section 3
reviews the data and our methodology, and Section 4
presents the finding of this study. Finally, Section 5
and Section 6
provide discussion and conclusion.
In this study, we examined poverty among vulnerable female householders in Korea using the concept of multidimensional poverty and investigated six dimensions: money, health, housing, employment, human relations, and social security. Poverty probabilities among female householders are classified through LCA and the relationships among the indicators. Our results can be summarized as follows.
First, when correlations among the six poverty dimensions were examined, the correlation between the monetary dimension and non-monetary dimensions was found to be insignificant. This implies that examining poverty solely from a monetary perspective will not fully cover life deficiencies, and thus, the estimated degree of actual poverty could be distorted. This study confirmed that adopting the multidimensional poverty measurement method can help provide more appropriate services to the poor than employing the existing money-oriented poverty measurement method and can thus contribute more to enhancing the overall quality of life.
Second, the LCA allowed us to divide female householders in Korea into three main poverty types. All of them are highly likely to experience poverty in terms of money and employment. Specifically, Type 2 is likely to experience basic poverty with a high probability of experiencing poverty only in terms of money and employment; this type accounts for about 51.02% of the respondents. Type 1 represents a complex poverty group with a high probability of experiencing poverty in terms of health and human relationships in addition to money and employment; this group accounts for 20.99% of all respondents. Type 3 is a health-vulnerable class with a high probability of experiencing health poverty in addition to money and employment; this group accounts for 27.98% of all respondents.
Third, when demographic characteristics based on the latent class type were examined, the average age of those in the poverty groups was found to be higher than that of the non-poverty group. In particular, it was the highest for Type 3, with a higher probability of health poverty. In terms of education level, the non-poverty group shows relatively high proportions of high school graduates and college graduates compared with the latent class types; there were no significant educational differences across the latent class types.
Therefore, a money deficit arising from labor and labor deficiencies is the major factor causing female householders’ poverty. In fact, most Korean female householders are engaged in temporary employment and part-time work (62.5%) and about 40% of female householders have experienced unemployment over the past year, demonstrating typical characteristics of the working poor who are incompletely involved in the labor market [41
]. Divorce and bereavement are the cause of an increase in the number of female householders [3
], and as women enter old age, the likelihood of a household becoming led by a woman rather than a man has increased, which has accelerated poverty in female householders [4
]. In this study, the average age of those in the poverty group (type 1 = 68.84, type 2 = 65.43, type 3 = 75.89) was significantly higher than that the non-poverty group (49.73). Thus, female householders are much more likely to live in poverty than other vulnerable groups because of the combined factors of being female and old age in the labor market.
Therefore, above all, the imperfections in the labor market need to be tackled. To secure stable employment, social jobs for elderly female householders should be expanded. In addition, because the pink-collar jobs (e.g., housework and care) in which women have traditionally been engaged are socially undervalued, new standards are needed to revalue them. To guarantee the economic independence of elderly female householders, social insurance should be changed to include unemployed female householders. In addition, for elderly female householders to participate in the labor market, the expansion of self-sufficiency projects should be considered.
We also recommend policy alternatives for each type. First, in the case of Type 2, employment expansion is necessary more than any other factor; if employment can be expanded, the probability of experiencing poverty in terms of money can be reduced to some extent. In the case of Type 3, employment expansion is not an appropriate policy, as this group is older and has a higher probability of health poverty. Thus, the focus should be on reducing their medical expenditure burden or offering them diverse medical benefits.
Distinguishing poverty groups using only a monetary standard could actually exclude from the defined policy target many who experience poverty [42
]. As can be seen from the results, distinguishing poverty groups through multidimensional poverty indicators allows us to infer that the poor are composed of several groups with different characteristics. Therefore, when establishing poverty policies, the fact that poverty groups are not a simple structural classification that can be distinguished by a single standard should be taken into consideration. In addition to ensuring income, policies should focus on other elements of poverty. Moreover, the target groups of these policies should be defined more broadly, applying multi-faceted standards in order not to exclude the poor that fall outside traditional categories.
Despite these significant findings, this study has some limitations that can be addressed in future research. First, the data used in this study include an oversampling of low-income households by 50%. Second, since the average age of those in the poverty group in this study was significantly higher than that in the non-poverty group, analyses should be conducted by age in future studies. Third, non-monetary dimensions were measured by respondents’ self-reported and therefore subjective evaluations. Previous studies have pointed out that measuring poverty subjectively does not necessarily provide objective evaluations of the poor; rather, it gives leeway to evaluate based on one’s feelings and can reflect multidimensional and non-objective situations [43
]. Thus, quantifying respondents’ perceptions on poverty dimensions might limit objective assessment. Future studies should develop indicators to measure non-monetary dimensions of poverty using objective norms.
In this study, we assessed female householders’ poverty in Korea using LCA and applied a multidimensional poverty approach to explore effective policy alternatives. All the three class types were found to be likely to experience poverty in terms of money and employment. Type 1 showed a high probability of poverty in terms of money, employment, human relations, and health; compared with Types 2 and 3, Type 1 had higher probabilities for several poverty indicators. Type 2 indicated basic poverty, with a high probability of experiencing poverty in terms of money and employment. Lastly, Type 3 had a higher probability of experiencing health poverty than Types 1 and 2. In the case of the non-poverty group, age was lower than in the poverty groups, while education level was higher. In addition, among the poverty groups, the average age was the highest for Type 3, which has the highest probability of experiencing poverty in terms of money, employment, and health.