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Monitoring Poverty Without Consumption Data : An Application Using the Albania Panel Survey




In developing countries, poverty is generally measured with expenditure data, which are normally available only every three to five years. In between surveys, there is a clear need to provide policy makers with information for the monitoring of poverty trends. This paper reviews several methods with which to perform this monitoring and compares the poverty estimates and trends resulting from their application to a panel data set for Albania. The results are broadly consistent across methods and point to an overall improvement in welfare conditions over time, concentrated in urban areas. Lacking a gold standard measure, the use of a suite of welfare indicators, if duly validated, can be a viable approach to monitor poverty trends. Caution should be exercised in drawing conclusions about the actual magnitudes of the changes.

Suggested Citation

  • Carlo Azzarri & Gero Carletto & Benjamin Davis & Alberto Zezza, 2006. "Monitoring Poverty Without Consumption Data : An Application Using the Albania Panel Survey," Eastern European Economics, Taylor & Francis Journals, vol. 44(1), pages 59-82, February.
  • Handle: RePEc:mes:eaeuec:v:44:y:2006:i:1:p:59-82

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    References listed on IDEAS

    1. Ravallion, Martin, 1996. "How Well Can Method Substitute for Data? Five Experiments in Poverty Analysis," World Bank Research Observer, World Bank Group, vol. 11(2), pages 199-221, August.
    2. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    3. Ravallion, Martin & Lokshin, Michael, 2002. "Self-rated economic welfare in Russia," European Economic Review, Elsevier, vol. 46(8), pages 1453-1473, September.
    4. David E. Sahn & David Stifel, 2003. "Exploring Alternative Measures of Welfare in the Absence of Expenditure Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 49(4), pages 463-489, December.
    5. Bidani, Benu & Ravallion, Martin, 1997. "Decomposing social indicators using distributional data," Journal of Econometrics, Elsevier, vol. 77(1), pages 125-139, March.
    6. Ravallion, Martin & Lokshin, Michael, 2001. "Identifying Welfare Effects from Subjective Questions," Economica, London School of Economics and Political Science, vol. 68(271), pages 335-357, August.
    7. Mark Montgomery & Michele Gragnolati & Kathleen Burke & Edmundo Paredes, 2000. "Measuring living standards with proxy variables," Demography, Springer;Population Association of America (PAA), vol. 37(2), pages 155-174, May.
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    Cited by:

    1. Jing Dai & Stefan Sperlich & Walter Zucchini, 2011. "Estimating and Predicting Household Expenditures and Income Distributions," MAGKS Papers on Economics 201147, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Baris Ucar, 2015. "The Usability of Asset Index as an Indicator of Household Economic Status in Turkey: Comparison with Expenditure and Income Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 121(3), pages 745-760, April.
    3. Gianni Betti & Ruzhdie Bici & Laura Neri & Thomas Pave Sohnesen & Ledia Thomo, 2017. "Local Poverty and Inequality in Albania," Department of Economics University of Siena 745, Department of Economics, University of Siena.
    4. Mauro Migotto & Benjamin Davis & Gero Carletto & Kathleen Beegle, 2005. "Measuring Food Security Using Respondents’ Perception of Food Consumption Adequacy," Working Papers 05-10, Agricultural and Development Economics Division of the Food and Agriculture Organization of the United Nations (FAO - ESA).
    5. Alberto Zezza & Gero Carletto & Benjamin Davis, 2005. "Moving Away from Poverty: A spatial analysis of poverty and migration in Albania," Working Papers 05-02, Agricultural and Development Economics Division of the Food and Agriculture Organization of the United Nations (FAO - ESA).
    6. World Bank, 2010. "Azerbaijan : Living Conditions Assessment Report," World Bank Other Operational Studies 2836, The World Bank.
    7. Luc Christiaensen & Peter Lanjouw & Jill Luoto & David Stifel, 2012. "Small area estimation-based prediction methods to track poverty: validation and applications," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(2), pages 267-297, June.
    8. Par Mardochée & Christian Mabi, 2015. "« Les actifs productifs influencent-ils le niveau de revenu en milieu rural ? Evidence empirique issue de Shabunda/Est de la RD Congo »," Working Papers hal-01202322, HAL.
    9. Pudney, Stephen & Francavilla, Francesca, 2006. "Income mis-measurement and the estimation of poverty rates: an analysis of income poverty in Albania," ISER Working Paper Series 2006-35, Institute for Social and Economic Research.
    10. Luisa Natali & Marta Moratti, 2012. "Measuring Household Welfare: Short versus long consumption modules," Papers inwopa671, Innocenti Working Papers.

    More about this item

    JEL classification:

    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes


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