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221013 ||| eng |
| 100 |
1 |
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|a Ersado, Lire
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| 245 |
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|a Azerbaijan's Household Survey Data
|h Elektronische Ressource
|b Explaining Why Inequality Is So Low
|c Ersado, Lire
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| 260 |
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|a Washington, D.C
|b The World Bank
|c 2006
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| 300 |
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|a 19 p.
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| 653 |
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|a Macroeconomics and Economic Growth
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| 653 |
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|a Household Income
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| 653 |
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|a Poverty Impact Evaluation
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| 653 |
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|a Human Development
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| 653 |
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|a Income On Food
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| 653 |
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|a Household Surveys
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| 653 |
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|a Small Area Estimation Poverty Mapping
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| 653 |
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|a Rural Development
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| 653 |
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|a Economic Growth
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| 653 |
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|a Household Consumption
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| 653 |
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|a Food Consumption
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| 653 |
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|a Rural Poverty Reduction
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| 653 |
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|a Inequality
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| 653 |
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|a Household Survey
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| 653 |
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|a Poverty Reduction
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| 653 |
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|a Services and Transfers to Poor
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| 653 |
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|a Consumption Expenditures
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| 653 |
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|a Consumption
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| 653 |
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|a Economic Theory and Research
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| 700 |
1 |
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|a Ersado, Lire
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b WOBA
|a World Bank E-Library Archive
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| 856 |
4 |
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|u http://elibrary.worldbank.org/content/workingpaper/10.1596/1813-9450-4009
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 330
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| 520 |
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|a While the Azerbaijan household income and expenditure survey (HIES) data satisfy most empirical regularities expected in a typical household survey data, the unequality measures based on the data are unusually low. For example, for the latest three years for which we have data (2002 - 2004), the consumption Gini coefficient (the commonly used summary measure of inequality) is in the range of 16 - 18 percent. This is among the lowest Gini coefficients ever observed in any country, and is extremely low even with the standard of countries generally considered as most equal in the world. Azerbaijan, a transitional economy with a significant natural resource base, is unlikely to be the most equal country in the world. The objective of this paper is to investigate why inequality measures are unusually low in the Azerbaijan household survey data. The author presents a methodology for diagnosing and identifying the potential sources of low inequality in the data, including cluster analysis at the primary sampling unit level. The main inference from the findings of the cluster analysis is that the observed low inequality indices are not due to poor supervision of the interviewers and the data collection process. The author finds that the main culprits for the observed low inequality in the HIES data are (1) the low participation rates of wealthy households in the household surveys, and (2) the widespread availability of well-targeted public and private transfers
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