本研究旨在探討莫拉克颱風與凡那比颱風期間村里所得與淹水之關係。國外許多文獻已經證實了低所得族群面臨較大的淹水機率，其理由是災區在經歷洪災後，房價下跌，高所得者為了生命財產安全選擇搬離災區，低所得者因為其經濟因素反而受到災區低房價吸引而搬入受災區，最終面臨較大的淹水機率。然而，不光淹水造成所得分布改變，所得亦有可能影響淹水機率，例如防洪設施的建造，有文獻提到在制定公共政策與資源分配時，具有高度政治權力的富有者會有自我圖利的現象，而我們想觀察是否在台灣防洪設施的建造也有此現象，高所得地區的淹水機率較低。
本文利用政府資料開放平台的村里界圖、地形圖、社會經濟資料服務平台的房價資料、財政部財政資訊中心的綜合所得資料，及國家災害防救科技中心的莫拉克颱風與凡那比颱風降雨分布及淹水地點進行分析，使用邏輯斯回歸(Logistic regression)與傾向分數配對法(Propensity score matching，PSM)控制降雨、地形、房價等變因狀況下，觀察所得對於淹水機率之影響，實證結果發現高所d淹水機率顯著低於對照組，因此我們可以推斷為政治力的因素所致。

This study investigate the relationship between flooding and income during Typhoon Morakot and Typhoon Fanapi. The literature had showed that the low-income group faces a large flooding risk. The reason is that the house price will fell where the areas was flooded, but the high-income people will move out for their safety. Then the low-income people were attracted by the low house price in the disaster-prone area and moved into those areas, eventually facing a larger flooding risk. However, not only the flooding changes the distribution of people who have various income, but people use their income to change the probability of flooding. For example, though the construction of public flood protection. Some paper confirmed that the rich people use their political power to benefit themselves by forming public policies and resource allocation.
This study used the open data of the map of the village and the terrain in the southern Taiwan, the house price, the income statistics, the rainfall distribution during Typhoon Morakot and Typhoon Fanapi, and the flooding during those Typhoon. The Logit model of flooding and the Propensity Score Matching (PSM)were adopted to control other factors of flooding and analyze the probability of flooding within areas where people have various income. We found that the flooding probability of the high-income areas were significantly lower than the low-income areas. The reason could be political power of high-income people.

Adger W.N. (1999). Social vulnerability to climate change and extremes in coastal Vietnam. World Development, 27(2), 249-269.
Bin O., Polasky S. (2004). Effects of flood hazards on property values: Evidence before and after Hurricane Floyd. Land Economics, 80(4), 490-500.
Caliendo M., Kopeinig S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31-72.
Cutter S.L. (1996). Vulnerability to environmental hazards. Progress in Human Geography, 20(4), 529-539.
Cutter S.L., Boruff B.J., Shirley W.L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242-261.
Davlasheridze M., Fan Q. (2017). Household Adjustments to Hurricane Katrina. Review of Regional Studies, 47(1), 93-112.
Felsenstein D., Lichter M. (2014). Social and economic vulnerability of coastal communities to sea-level rise and extreme flooding. Natural Hazards, 71(1), 463-491.
Kousky C. (2010). Learning from Extreme Events: Risk Perceptions after the Flood. Land Economics, 86(3), 395-422.
Krueger A.O. (1974). The political economy of the rent-seeking society. The American economic review
64(3), 291-303.
Logan J.R., Issar S., Xu Z. (2016). Trapped in place? Segmented resilience to hurricanes in the Gulf Coast, 1970–2005. Demography, 53(5), 1511-1534.
McCaughey J.W., Daly P., Mundir I., Mahdi S., Patt A. (2018). Socio-economic consequences of post-disaster reconstruction in hazard-exposed areas. Nature Sustainability, 1(1), 38-43.
Orton M., Rowlingson K. (2007). A problem of riches: Towards a new social policy research agenda on the distribution of economic resources. Journal of Social Policy, 36(1), 59-77.
Piketty T. (2015). About capital in the twenty-first century. American Economic Review, 105(5), 48-53.
Rasch R. (2017). Income Inequality and Urban Vulnerability to Flood Hazard in Brazil. Social Science Quarterly, 98(1), 299-325.
Rosenbaum P.R., Rubin D.B. (1983). The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika, 70(1), 41-55.
Rossi M.A. (2014). The impact of individual wealth on posterior political power. Journal of Economic Behavior & Organization, 106, 469-480.
Rubin D.B. (2001). Using propensity scores to help design observational studies: application to the tobacco litigation. Health Services & Outcomes Research Methodology, 2(3-4), 169-188.
Schneiderbauer S., Ehrlich D. (2004). Risk, hazard and people’s vulnerability to natural hazards. European Commission Joint Research Centre, 21410, 40.
Smith V.K., Carbone J.C., Pope J.C., Hallstrom D.G., Darden M.E. (2006). Adjusting to natural disasters. Journal of Risk and Uncertainty, 33(1-2), 37-54.
Tompkins E.L., Lemos M.C., Boyd E. (2008). A less disastrous disaster: Managing response to climate-driven hazards in the Cayman Islands and NE Brazil. Global Environmental Change-Human and Policy Dimensions, 18(4), 736-745.