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Using panel data, this paper analyzes the impact of high inflation on household livelihoods in urban South Sudan. Based on a difference-in-difference approach, inflation is found to have a strong negative impact on urban poverty between 2015 and 2017, mainly driven by the increase of non-food prices. Food price inflation had a negative and statistically significant impact on girls' primary and secondary school attendance, while proximity to school is very important for girls' school attendance. Increases in food prices led to a decline in labor force participation, increasing unemployment among urban residents. Inflation is exacerbating food insecurity and hunger, particularly for the poorest households who are more vulnerable to hunger. Inflation has also negatively affected households' perceptions of welfare. These changes in welfare are mostly explained by the period of near hyper-inflation in 2017. Addressing high inflation must be at the center of efforts to reduce poverty and hunger to improve the welfare of the people of South Sudan.
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Interviewer design effects occur when data collected by the same interviewer is more similar than data collected by different interviewers. Design effects inflate survey variance and reduce the precision of estimates. Using household survey data collected via computer assisted personal interviewing (CAPI) in Sudan this paper employs a two-level mixed effects regression model to identify interviewer design effects for key variables. The study finds mean interviewer design effect values of 7 with a maximum of 16, implying a significant loss of precision. Recommendations to mitigate interviewer design effects include simplifying questions, sound survey implementation practices, and utilizing multi-way cluster robust standard errors to account for both area and interviewer clustering during data analysis.
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This study seeks to support the efforts of Sudan in the targeting of the Sudan Emergency Safety Nets Project (SESNP) and any other future safety net programs in Sudan to those most in need. Sudan has faced numerous challenges for several years. Since its separation from South Sudan in 2011, the economy has experienced macroeconomic imbalances that have lasted for over a decade. In addition, the country has faced political instability, internal conflicts, and challenging climatic conditions. All of these challenges pose direct consequences to the poor. More recently, the onset of the COVID-19 pandemic and the Russia-Ukraine crisis have only exacerbated the economic and social situation in the country. In this context, the number of poor and vulnerable is expected to have increased considerably since the last reported official poverty rate, which accounted for 61.1% of the population in 2015. In light of these events, there is a growing consensus on the need of social safety net programs in the country. The proposed program, the SESNP, is expected to provide unconditional cash and food transfers to nearly 2 million Sudanese people (i.e., about 5% of the population). To support this program in targeting beneficiaries to improve the poverty impact of the program, we develop a Proxy Mean Tests (PMT) for Sudan based on the National Household Budget and Poverty Survey (NHBPS) 2014/2015. The results indicate that the use of a PMT could considerably improve the program in reaching those most in need, while reducing expenditure towards those with adequate resources. This could improve both the poverty impact, as well as the sustainability of the program.
Consumption (Economics) --- Poverty --- Economic development projects --- Surveys. --- Management.
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