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This paper assesses the effects of donor-assisted projects in impoverished communities through an assessment of the ARMM Social Fund Project. The program was first assessed on its design features and then by measuring their impact on several welfare indicators. The use of simple regression techniques determined the effect of intervention variables on their respective welfare indicators. Results of the regression analysis offers mixed results on the effects of the intervention, which is still open for further discussion. The paper suggests that more robust results would emerge if certain aspects of the project's design were modified. This paper assesses the effects of donor-assisted projects in impoverished communities through an assessment of the ARMM Social Fund Project. The program was first assessed on its design features and then by measuring their impact on several welfare indicators. The use of simple regression techniques determined the effect of intervention variables on their respective welfare indicators. Results of the regression analysis offers mixed results on the effects of the intervention, which is still open for further discussion. The paper suggests that more robust results would emerge if certain aspects of the project's design were modified. Using the data from the Quality Improvement Demonstration Study (QIDS), this study examines the determinants of child health in the provinces of Region 6 (Iloilo, Capiz, Negros Occidental), Region 7 (Cebu, Bohol, Negros Oriental), Region 8 (Leyte, Eastern Samar) and the islands of Biliran, Siquijor, and Camiguin. Specifically, we seek to provide an indirect assessment of the impact of public health commodities which are typically provided for by the government such as health facilities, water, sanitation, prenatal care, including breastfeeding and immunization programs. We use two measures of child health outcomes - anthropometric measures and self-reported health assessments by the mother. For the anthropometries, we use standardized z-scores for height-for-age (stunting), weight-for-height (wasting), and weight-for age (underweight) of children based on a reference population. Logistic regression was used for the analysis of anthropometric measures while Ordered Probit was used for the self-reported health assessments by the mother. The regression results for the anthropometric measures indicate that child and household characteristics such as maternal education and monthly income strongly affect child health, although these results vary across anthropometric parameters. Access to health facilities also positively affect child health indicated by doctor in-charge of delivery of baby and birth weight, a proxy variable for access to prenatal care. Moreover, breastfeeding and immunization also seem to be significantly associated with child health outcomes. Similarly, child health as measured by mother-reported health status is also correlated with child and household characteristics such as age and household size, respectively. Health infrastructure, particularly the presence of piped water system and sanitary toilet, are shown to be significant correlates of child health. Public health commodities which are typically provided for by the government, such as access to health facilities, health infrastructure, immunization and breastfeeding are shown to improve child health outcomes. The analysis of the determinants of child heath points to the importance not only of the common correlates of child health particularly maternal education and family resources but also to the significance of community variables and access to public health commodities. Our study is helpful to policy makers, stakeholders, advocates and researchers who wish to obtain an understanding of the determinants of child health and the impacts of public health commodities on child health. It also makes a case in support of child health investments, as a way of securing positive health outcomes for children's well-being and by extension, improving our human capital and influencing the direction and quality of development in the country.

The effects of government spending on poverty have been studied in the past by individually measuring the impact of each capital investment on poverty. There is also an apparent shortage of literature about how the government, through its fiscal policy tool that is government spending, is able to reduce the poverty in the Philippines especially in the rural areas where most of the poor reside. Thus, this paper, using the framework developed by Fan and his colleagues, establishes a simultaneous equations model linking public investments in agricultural research and development, roads, education and irrigation with poverty. The results show that urbanization, development of non farm employment and increases in agricultural productivity have negative and statistically significant impact on rural poverty reduction. Of these three factors, however, agricultural productivity contributes the most to poverty alleviation. Analyzing further in terms of returns in agricultural productivity and poverty reduction, the estimates reveal that investments in agricultural R&D yield the highest marginal returns. Therefore, spending in agricultural R&D contributes the most to agricultural productivity and poverty alleviation.

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