{"title":"Spatial Analysis of Poverty Incidence and Road Networks in Eastern Visayas Region, Philippines","authors":"Hernan Pantolla, Nelda Atibagos-Nacion","doi":"10.56899/152.04.01","DOIUrl":null,"url":null,"abstract":"Poverty is a prevailing challenge in the Philippines. Through the small area estimation (SAE) of the Philippine Statistics Authority, the poor cities and municipalities with poor households were identified. Some locations are also vulnerable to natural calamities and have limited resources. The 2018 SAE shows that the region of Eastern Visayas is one of the poorest in the country. Moreover, the region is vulnerable to natural hazards, particularly typhoons. The regional road network is also less connected for the poorer municipalities. Hence, slow economic growth is a concerted outcome. To provide an evidence-based framework on potentially optimized resource allocation of, say, government institutions and humanitarian organizations in countering these poverty concerns exacerbated by natural calamities, this paper used the geographical information system (GIS) for easier visualization and interpretability. Spatial analyses were also applied to [1] determine if clusters of poverty exist in the region across different periods and [2] if hot spots of poverty incidence exist in the latest SAE. The findings reveal that poverty incidence for all four previous periods of SAE has significant non-random clusters. In addition, poverty hot spots, at varying confidence levels, were statistically identified. These hot spots are also vulnerable to frequent typhoons and have limited access to national roads. Additionally, the bootstrap regression shows that economic growth could be boosted by expanding road networks as an indicator of decreased poverty incidence. This study, thus, further emphasizes the importance of data-driven decision-making, particularly in efforts to counter poverty, including some of its aggravating external factors such as natural calamities. The application of empirical methods in formulating and improving policies, especially those related to infrastructure investments and expansions, is also recommended, given the limited resources. It also highlights how road networks in the region could be instrumental in promoting economic progress, particularly in less accessible areas.","PeriodicalId":39096,"journal":{"name":"Philippine Journal of Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Philippine Journal of Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56899/152.04.01","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Multidisciplinary","Score":null,"Total":0}
引用次数: 0
Abstract
Poverty is a prevailing challenge in the Philippines. Through the small area estimation (SAE) of the Philippine Statistics Authority, the poor cities and municipalities with poor households were identified. Some locations are also vulnerable to natural calamities and have limited resources. The 2018 SAE shows that the region of Eastern Visayas is one of the poorest in the country. Moreover, the region is vulnerable to natural hazards, particularly typhoons. The regional road network is also less connected for the poorer municipalities. Hence, slow economic growth is a concerted outcome. To provide an evidence-based framework on potentially optimized resource allocation of, say, government institutions and humanitarian organizations in countering these poverty concerns exacerbated by natural calamities, this paper used the geographical information system (GIS) for easier visualization and interpretability. Spatial analyses were also applied to [1] determine if clusters of poverty exist in the region across different periods and [2] if hot spots of poverty incidence exist in the latest SAE. The findings reveal that poverty incidence for all four previous periods of SAE has significant non-random clusters. In addition, poverty hot spots, at varying confidence levels, were statistically identified. These hot spots are also vulnerable to frequent typhoons and have limited access to national roads. Additionally, the bootstrap regression shows that economic growth could be boosted by expanding road networks as an indicator of decreased poverty incidence. This study, thus, further emphasizes the importance of data-driven decision-making, particularly in efforts to counter poverty, including some of its aggravating external factors such as natural calamities. The application of empirical methods in formulating and improving policies, especially those related to infrastructure investments and expansions, is also recommended, given the limited resources. It also highlights how road networks in the region could be instrumental in promoting economic progress, particularly in less accessible areas.