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Estimating poverty over time and space: Construction of a time-variant poverty index for Costa Rica

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  • Cavatassi, Romina
  • Davis, Benjamin
  • Lipper, Leslie

Abstract

This paper presents the construction of a spatially explicit, nationally disaggregated measure of poverty over time in Costa Rica. The paper first describes the two possible methods considered for the construction of a poverty map: principal component ana

Suggested Citation

  • Cavatassi, Romina & Davis, Benjamin & Lipper, Leslie, 2004. "Estimating poverty over time and space: Construction of a time-variant poverty index for Costa Rica," ESA Working Papers 23791, Food and Agriculture Organization of the United Nations, Agricultural Development Economics Division (ESA).
    • Handle: RePEc:ags:faoaes:23791
    DOI: 10.22004/ag.econ.23791
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    1. Filmer, Deon & Pritchett, Lant, 1998. "Estimating wealth effects without expenditure data - or tears : with an application to educational enrollments in states of India," Policy Research Working Paper Series 1994, The World Bank.
    2. Nicholas Minot & Bob Baulch, 2005. "Poverty Mapping with Aggregate Census Data: What is the Loss in Precision?," Review of Development Economics, Wiley Blackwell, vol. 9(1), pages 5-24, February.
    3. Bigman, David, et al, 2000. "Community Targeting for Poverty Reduction in Burkina Faso," The World Bank Economic Review, World Bank, vol. 14(1), pages 167-193, January.
    4. Skoufias, Emmanuel & Davis, Benjamin & de la Vega, Sergio, 2001. "Targeting the Poor in Mexico: An Evaluation of the Selection of Households into PROGRESA," World Development, Elsevier, vol. 29(10), pages 1769-1784, October.
    5. Minot, Nicholas, 2000. "Generating Disaggregated Poverty Maps: An Application to Vietnam," World Development, Elsevier, vol. 28(2), pages 319-331, February.
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    Cited by:

    1. Andam, Kwaw S. & Ferraro, Paul J. & Holland, Margaret B., 2009. "What are the social impacts of land use restrictions on local communities? Empirical evidence from Costa Rica," 2009 Conference, August 16-22, 2009, Beijing, China 51783, International Association of Agricultural Economists.
    2. 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.
    3. Ayala Wineman, 2016. "Multidimensional Household Food Security Measurement in Rural Zambia," Agrekon, Taylor & Francis Journals, vol. 55(3), pages 278-301, July.
    4. Canavire-Bacarreza, Gustavo & Hanauer, Merlin M., 2013. "Estimating the Impacts of Bolivia’s Protected Areas on Poverty," World Development, Elsevier, vol. 41(C), pages 265-285.
    5. Tsehay, Abrham Seyoum & Bauer, Siegfried, 2012. "Poverty Dynamics and Vulnerability: Empirical Evidence from Smallholders in Northern Highlands of Ethiopia," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126873, International Association of Agricultural Economists.
    6. Abera Demeke & Alwin Keil & Manfred Zeller, 2011. "Using panel data to estimate the effect of rainfall shocks on smallholders food security and vulnerability in rural Ethiopia," Climatic Change, Springer, vol. 108(1), pages 185-206, September.
    7. Wineman, Ayala, 2016. "Multidimensional Household Food Security Measurement in Rural Zambia," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 55(3), September.
    8. Rie Muraoka & Hsiaoping Chien & Minjuan Zhao, 2023. "Production and Market Participation of Buckwheat Farmers: Micro-Evidence from Shaanxi Province, China," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    9. Yuan Zhao & Ronak Paul & Sean Reid & Carolina Coimbra Vieira & Chris Wolfe & Yan Zhang & Rumi Chunara, 2024. "Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(2), pages 639-657, November.
    10. Paul Ferraro & Merlin Hanauer, 2011. "Protecting Ecosystems and Alleviating Poverty with Parks and Reserves: ‘Win-Win’ or Tradeoffs?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(2), pages 269-286, February.
    11. Guie Li & Zhongliang Cai & Ji Liu & Xiaojian Liu & Shiliang Su & Xinran Huang & Bozhao Li, 2019. "Multidimensional Poverty in Rural China: Indicators, Spatiotemporal Patterns and Applications," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(3), pages 1099-1134, August.
    12. Tsehay, Abrham Seyoum & Bauer, Siegfried, 2012. "Poverty and Vulnerability Dynamics: Empirical Evidence from Smallholders in Northern Highlands of Ethiopia," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 51(4), pages 1-32, November.
    13. Shadbolt, Nicola & Siddique, Muhammad Imran & Tozer, Peter, 2019. "Measuring how NZ dairy farmers react to volatile prices by analysing farmer responses over a period of time using panel data," 22nd Congress, Tasmania, Australia, March 3-8, 2019 345899, International Farm Management Association.
    14. Sandeep Kumar & Snehashish Chakraverty & Narayan Sethi, 2023. "Multidimensional Poverty: CMPI Development, Spatial Analysis and Clustering," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 169(1), pages 647-670, September.

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    More about this item

    Keywords

    ;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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