Measuring Poverty Dynammics and Inequality in Transition Economies : Disentangling Real Events from Noisy Data
The author uses instrumental variable methods, and the decomposition of income into transitory and persistent components to distinguish underlying income inequality and changes in poverty from the effects attributable to measurement error or transi...
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| Format: | Policy Research Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2014
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2001/02/1003132/measuring-poverty-dynammics-inequality-transition-economies-disentangling-real-events-noisy-data http://hdl.handle.net/10986/19701 |
| Summary: | The author uses instrumental variable
methods, and the decomposition of income into transitory and
persistent components to distinguish underlying income
inequality and changes in poverty from the effects
attributable to measurement error or transitory shocks. He
applies this methodology to household-level panel data for
Russia and Poland in the mid-1990s. The author finds that:
1) Accounting for noise in the data reduces inequality (as
measured by the Gini coefficient) by 10-45 percent. 2)
Individuals in both countries face much economic insecurity.
The median absolute annual change in income or spending is
about fifty percent in Russia, and about 20 percent in
Poland. But roughly half of these fluctuations reflect
measurement error or transitory shocks, so underlying levels
of income, and spending are much more stable than the data
suggest. 3) The apparent high levels of economic mobility
are driven largely by transitory events and noisy data.
After transitory shocks are accounted for, about eighty
percent of the poor in both Russia and Poland remain in
poverty for at least one year. So there is a real risk of an
entrenched underclass emerging in these transition economies. |
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