Predicting the rental value of houses in household surveys in Tanzania, Uganda and Malawi: Evaluations of hedonic pricing and machine learning approaches.

Housing value is a major component of the aggregate expenditure used in the analyses of welfare status of households in the development economics literature. Therefore, an accurate estimation of housing services is important to obtain the value of housing in household surveys. Data show that a significant proportion of households in a typical Living Standard Measurement Survey (LSMS), adopted by the Word Bank and others, are self-owned. The standard approach to predict the housing value for such surveys is based on the rental cost of the house. A hedonic pricing applying an Ordinary Least Squares (OLS) method is normally used to predict rental values. The literature shows that Machine Learning (ML) methods, shown to uncover generalizable patterns based on a given data, have better predictive power over OLS applied in other valuation exercises. We examined whether or not a class of ML methods (e.g. Ridge, LASSO, Tree, Bagging, Random Forest, and Boosting) provided superior prediction of rental value of housing over OLS methods accounting for spatial autocorrelations using household level survey data from Uganda, Tanzania, and Malawi, across multiple years. Our results showed that the Machine Learning methods (Boosting, Bagging, Forest, Ridge and LASSO) are the best models in predicting house values using out-of-sample data set for all the countries and all the years. On the other hand, Tree regression underperformed relative to the various OLS models, over the same data sets. With the availability of abundant data and better computing power, ML methods provide viable alternative to predicting housing values in household surveys.

Women's Empowerment and Infant and Child Health Status in Sub-Saharan Africa: A Systematic Review.

INTRODUCTION: Although many studies have examined the relationship between women's empowerment and a wide range of health outcomes, the extent to which the different dimensions of empowerment influence children's health, and through which mechanisms and in what contexts, is limited in sub-Saharan Africa. The objective of this review is to systematically assess and examine studies that investigated the association between women's empowerment and children's health status in sub-Saharan Africa. METHODS: A systematic review of the published literature is searched through PubMed, Google Scholar, Embase, Web of Science and Scopus databases focusing on different measures of women's empowerment and children's health outcomes. Inclusion criteria in the review are studies that are published in English; full and original articles; studies measuring at least one dimension of women's empowerment and children's health outcomes; and Sub-Saharan African context. Studies included in this review are articles published between the year 2000 and 2019. Studies were excluded if the source was a letter, editorial, review, commentary, abstracts without providing full information about the study. RESULTS: Initially 4718 citations were identified. Finally, 15 studies met the inclusion and exclusion criteria. In general, the evidence suggests that women's empowerment at the household level is positively and statistically significantly associated with better children's health outcomes in sub-Saharan African countries. The review also reveals that women's decision-making power or autonomy is the most common measure of women's empowerment employed by many studies. CONCLUSIONS: Future related studies would benefit by incorporating additional aspects of women's empowerment and child health outcomes.

Associations between women's empowerment and children's health status in Ethiopia.

Although women's empowerment has gained attention over the last two decades, our understanding of the associations between different dimensions of women's empowerment and different children's health outcomes is limited. This study aims to measure the extent of women's empowerment and to examine its associations with the children's health status in Ethiopia. Data were obtained from the 2016 Ethiopian Demographic and Health Survey (EDHS). The sample is restricted to a sub-sample of 10,641 women from 15 to 49 years old and their children under the age of five years. We used children's height-for-age and weight-for-height Z-scores and pneumonia and anemia experience as indicators of children's health outcome. Women's empowerment is measured by five indices reflecting their participation in decision-making, attitudes towards wife-beating by husband, barriers to health care access, asset ownership, and socio-economic variables. These indicators of empowerment were constructed using exploratory and confirmatory factor analysis. A Multiple Indicators Multiple Causes (MIMIC) model was employed to examine the relationship between women's empowerment and latent child health outcomes, after controlling for relevant covariates. Results suggests that enhancing women's empowerment in the household in terms of their socio-economic status (i.e., increasing women's access to education, information, media, and promoting saving) was associated with less likelihood of the children's being stunted or wasted (p<0.05). Higher women's empowerment in terms of household decision-making power were also associated with better children's health status measured by the children's experience of pneumonia and anemia (p<0.05). All aspects of women's empowerment are not related with children's health indicators. Women's empowerment dimensions related with child health have a varying degree of association with the different children's health indicators. Gender-specific policies focusing on increasing women's access to education, media, information, and promoting saving and their participation in the household decision making are some of the strategies for improving their children's health and wellbeing.