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MEASURING POVERTY IN RUSSIA: POSSIBILITIES AND LIMITATIONS

Abstract

The article analyses prospects for incorporating multidimensional poverty indicators into Russian statistical practice. The advantages and disadvantages of one-dimensional and multidimensional approaches to measuring poverty are discussed. The authors place emphasis on the combination of both monetary and non-monetary indicators of poverty using workings of the UN Statistical Commission and the World Bank. Among monetary indicators special attention is given to «consumer expenditures» aggregate.
It is demonstrated that there is a discrepancy between estimates of well-being indicators sourced from household surveys and obtained when calculating the system of national accounts. The issue of selecting poverty and well-being projections to calculate multidimensional indices agreeing with modern Russian conditions is reviewed. The authors underline the special importance of health indicators with regard to poverty characteristics. They also discuss ways to aggregate information on the poor into the final poverty index.
Attention is paid to the Rosstat’s surveys on income, expenditure and living conditions of the population as sources of information for constructing multidimensional poverty index, material deprivation and social exclusion. The conclusion is made that these surveys provide enough information to base on them the multidimensional poverty index that meets the requirements of international statistics, provided that there is completeness and regularity of data collection. The method for calculating MPI [Alkire-Foster (AF) method] is illustrated in the article on the data of the notional example.

About the Authors

Irina I. Eliseeva
Saint-Petersburg State University of Economics
Russian Federation
(St. Petersburg, Russia)


Yulia V. Raskina
European University at St. Petersburg
Russian Federation
(St. Petersburg, Russia)


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Review

For citations:


Eliseeva I.I., Raskina Yu.V. MEASURING POVERTY IN RUSSIA: POSSIBILITIES AND LIMITATIONS. Voprosy statistiki. 2017;(8):70-89. (In Russ.)

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