Ländliche Armut in Indonesien: Indikatoren, Dynamik und Verbindung zur Entwaldung

This thesis aims at analyzing three aspects of rural poverty in Central Sulawesi, Indonesia: Its aim is to assess the robustness of two operational poverty assessment models developed in 2005 for Central Sulawesi. It thus contributes to the discussion on the rationale for operational poverty assessment by proxy-means tests. Furthermore, the study aims to gain a better understanding of the poverty dynamics in the region and it is the most recent contribution to the to this topic in the Indonesian context. Additionally, the study explores the link between rural poverty and deforestation at the household level in the research area. The analyses are based on primary data obtained from household surveys on expenditures and income in the vicinity of the Lore Lindu National Park in Central Sulawesi. In 2005, two very promising operational poverty assessment models were developed for Central Sulawesi using 15 proxy indicators to predict absolute poverty. In 2007, both models were tested regarding the extent to which these models are robust over time in terms of prediction power and in terms of their indicator composition. In addition, an indicator based poverty assessment tool provided by the U.S. Agency for International Development (USAID) for Indonesia was evaluated here using the data set from Central Sulawesi. Regarding the robustness of indicator-based poverty assessment by proxy-means tests, the sets of indicators derived in 2005 were still capable of detecting the very poor households (those living on less then 1 Dollar purchasing power parities per capita and day) in 2007. However, the models tend to over-predict the very poor. For the assessment of absolute poverty in the research area, we recommend the use of 15 easy to verify indicators (Model 2) in combinati! on with the quantile coefficients of these indicators derived from the one-step procedure (estimated in 2005). This is based on the comparison of accuracy performance of all tools in both years. The accuracy levels of the two models tested remain similar when estimated using the 2007 dataset. However, the indicator composition of the tools changed. The nationally calibrated tool provided by USAID is shown to perform poorly in terms of accuracy when applied to our data set. To gain a better understanding of the poverty dynamics in the region, different measures of poverty are compared between the survey years of 2005 and 2007. Additionally, transitions into and out of poverty are obtained. The results show that people in the research area got poorer between 2005 and 2007 since significantly more people are shown to slipped into expenditures below the 2 USDollar-poverty line. Moreover, the poverty deficit in 2007 is also shown to be greater than the poverty deficit of 2005 irrespective of which poverty line is used. While 49 percent of the very poor households remain very poor in both survey years, 33 percent of them moved out of severe poverty but still had to live on less than 2 USDollar PPP per capita and day. Nonetheless there is also movement in the opposite direction. 23 percent of the households in the category of poor (living on less than 2 USDollar-poverty line) in 2005, became severely poor (less than 1 USDollar-poverty line) in 2007. To trace the underlying determinants of chronic and transitory poverty, multi-nominal logit regression analyses were applied. Results show that large households are more likely to be chronically and transitorily very poor. They are also shown to have higher probability of being chronically poor. Lack of access to electricity also makes severe chronic and transitory poverty, as well as chronic poverty more probable. Household without access to social capital are similarly more likely to get chronically very poor. Access to credit reduces the probability of becoming chronically very poor and also makes chronic and transient poverty less likely. Household without access to remittances from relatives working away from home are also more prone to (severe) chronic poverty. Finally, lack of opportunities to engage in non-agricultural income generating activities increases the probability to become chronically or transitorily very poor. The results from the study on the linkage between poverty and deforestation suggests that conversion of forest into farm land in the research area is indeed a severe problem. Approximately 52 km2 of forest area was converted into farm land between 1999 and 2006 by smallholders. While the poorest and the poor mainly replace forests with subsistence crops such as maize and dry rice, the wealthier households mainly grow cocoa. The findings also show that poorer households are more likely to clear forest than their wealthier counterparts. However, most of the area converted is dedicated to cocoa production. Furthermore, households with younger household heads tend to clear more forest area than households with older household heads. Interestingly, access to social capital tends to increase deforestation. Secure property rights, however, tend to reduce deforestation. Additionally, the location of the household plays a crucial role: households living in a sub-district closer at th! e forest boarder are more likely to clear forest than those located further away.