比较交叉调查微观归因与宏观预测技术:革命后突尼斯的贫困问题

Jose Cuesta, G. Ibarra
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引用次数: 8

摘要

突尼斯长期以来一直是减贫成就和有利于贫困人口增长的典范。然而,在贫困率减半之后,2011年初的一场革命震惊了世界,从那时起,人们对其贫困水平一无所知。为了填补这一空白,本分析开发并比较了多个交叉调查的微观估算(使用家庭预算和劳动力调查)与宏观贫困预测(基于部门国内生产总值、失业率和通货膨胀)。这两种技术的结果都很可靠:突尼斯革命后的贫困在2011年首先增加,然后在2012年减少。这种波动幅度在1%到2.3%之间波动,主要发生在城市地区。使用现成的宏观行政数据的方法所提供的贫穷水平和趋势的估计,与在分析上更为复杂和需要微观推算技术的数据所提供的估计非常接近。突尼斯的这些调查结果为缺乏数据的情况提供了相关的见解,这些情况在福利统计的频率和可获得性方面存在严重缺陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia
Tunisia was showcased for a long time as an example of poverty reduction achievement and pro-poor growth. Yet, after halving its poverty rates a revolution took the world by surprise early in 2011 and since then nothing is known about its poverty levels. To fill that gap, this analysis develops and compares multiple cross-survey micro imputations (using household budgetary and labor force surveys) with macro poverty projections (based on sector GDP, unemployment and inflation). Results from both techniques are robust: poverty in post revolution Tunisia first increased in 2011 to then decrease in 2012. The magnitude of this swing oscillates between 1 and 2.3 percent points and accrues mostly from urban areas. Methods using readily available macro administrative data provide estimates of poverty levels and trends very close to those provided by analytically more sophisticated and data demanding micro imputation techniques. These findings for Tunisia provide relevant insights in data deprived contexts with serious deficiencies in the frequency and accessibility of welfare statistics.
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