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NATIONAL CENSUS (2) answer(s).
 
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ID:   130972


China's urban employment and urbanization rate: a re-estimation / Wang, Xiaolu; Wan, Guanghua   Journal Article
Wan, Guanghua Journal Article
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Publication 2014.
Summary/Abstract The present paper argues that China's existing population and employment statistics are misleading, and have failed to include many of the migrant and labor force flows between urban and rural areas. The paper reconciles the differences between official census data and other survey statistics and attempts to recalculate China's urban population and employment figures. Our analyses indicate that official statistics of 2012 underestimate China's urban employment by approximately 47 million while overestimating rural employment by 31 million. The adjusted urbanization rate exceeded 55 percent in 2012, almost 3 percentage points higher than the official statistics. Nevertheless, there remains much potential for rural-to-urban migration. More specifically, if the current bottlenecks in household registration, social security and public welfare systems can be removed or relaxed, China's urbanization rate could rise by another 10 percentage points or even more over the next decade.
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2
ID:   115241


How geographically concentrated is poverty in Fiji? / Pabon, Laura; Umapathi, Nithin; Waqavonovono, Epeli   Journal Article
Pabon, Laura Journal Article
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Publication 2012.
Summary/Abstract In this paper, we present highly disaggregated estimates of expenditure-based poverty in Fiji using data from the 2007 national census and 2008-2009 Household Income and Expenditure Survey. Predicted poverty is estimated at provincial and tikina levels. Poverty in Fiji is marked by considerable spatial heterogeneity that cannot be gauged by the division level household survey estimates revealing pockets of poverty even within relatively well-off regions. Predicted poverty is highest in Cakaudrove province in Northern Division. Most strikingly, we find that 50% of all the poor in Fiji are concentrated in just 6 out of 85 tikinas, namely Suva, Labasa, Ba, Naitasiri, Vuda and Nadi. This finding has important implications for efficiency of targeted poverty alleviation programmes. We also focus on squatter settlements for which poverty headcount estimates using the Household Income and Expenditure Survey are not feasible. We find these settlements have rates of poverty headcount ratio that range from 38-55% depending on the Division the squatter settlement is located in; this range is significantly higher compared with the average urban poverty estimated at 26% and raises important social policy issues for addressing urban poverty.
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