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Consumption growth and spatial poverty traps: an analysis of the effects of social services and community infrastructures on living standards in rural Peru

Author

Listed:
  • Philippe De Vreyer

    () (Université de Lille II, DIAL)

  • Javier Herrera

    () (DIAL, IRD, Paris)

  • Sandrine Mesplé-Somps

    () (DIAL, IRD, Paris)

Abstract

We test the effect of local geographic endowment of capital on household growth in living standards in rural Peru, using a four years unbalanced panel data set. Our theoretical model of household consumption growth allows for the effect of community variables to modify the returns to augmented capital in the household production function. Data are coming from three different sources: ENAHO 1997-2000 household surveys, the population census of 1993 and the district infrastructure census of 1997. Altogether the addition of these different data sources makes an unusually rich data set, at least when considered with developing country standards. As in Jalan and Ravallion (2002), we use a quasi-differencing method to identify the impact of locally determined geographic and socioeconomic variables, while removing unobserved household and community level fixed effects. GMM are then used to estimate the model parameters. Several significant interesting results appear, confirming that private consumption growth depends on local geographic variables. _________________________________ A partir d’un panel non cylindré de 4 années nous testons l’effet du capital géographique local sur la croissance du bien-être des ménages ruraux au Pérou. Le modèle théorique de croissance de la consommation autorise les variables mesurées au niveau communautaire à modifier le rendement du capital augmenté dans la fonction de production du ménage. Les données proviennent de trois sources : les enquêtes ménages ENAHO 1997-2000, le recensement de la population de 1993 et le recensement sur les infrastructures des municipalités de 1997. L’ensemble constitue une base de données d’une richesse exceptionnelle dans le contexte d’une économie en développement. A l’instar de Jalan et Ravallion (2002), nous utilisons la méthode de quasi-différenciation pour identifier les effets des variables géographiques tout en éliminant les effets fixes géographiques et individuels inobservés. L’estimation est effectuée moyennant l’emploi de la méthode des moments généralisés. Plusieurs résultats intéressants sont obtenus, confirmant l’hypothèse selon laquelle la croissance de la consommation des ménages dépend de facteurs géographiques locaux.

Suggested Citation

  • Philippe De Vreyer & Javier Herrera & Sandrine Mesplé-Somps, 2002. "Consumption growth and spatial poverty traps: an analysis of the effects of social services and community infrastructures on living standards in rural Peru," Working Papers DT/2002/17, DIAL (Développement, Institutions et Mondialisation), revised Oct 2003.
  • Handle: RePEc:dia:wpaper:dt200217
    as

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    File URL: http://www.dial.ird.fr/media/ird-sites-d-unites-de-recherche/dial/documents/publications/doc_travail/2002/2002-17
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    References listed on IDEAS

    as
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    Cited by:

    1. Dercon, Stefan, 2004. "Growth and shocks: evidence from rural Ethiopia," Journal of Development Economics, Elsevier, vol. 74(2), pages 309-329, August.
    2. Grimm, Michael & Gräb, Johannes, 2007. "Robust Multiperiod Poverty Comparisons," Proceedings of the German Development Economics Conference, Göttingen 2007 8, Verein für Socialpolitik, Research Committee Development Economics.
    3. Johannes Gräb & Michael Grimm, 2008. "Spatial inequalities explained - Evidence from Burkina Faso," Ibero America Institute for Econ. Research (IAI) Discussion Papers 173, Ibero-America Institute for Economic Research.
    4. David Stifel & Bart Minten, 2008. "Isolation and agricultural productivity," Agricultural Economics, International Association of Agricultural Economists, vol. 39(1), pages 1-15, July.
    5. Michael Grimm, 2007. "Removing the anonymity axiom in assessing pro-poor growth," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(2), pages 179-197, August.

    More about this item

    Keywords

    Politiques de lutte contre la pauvreté; croissance; externalités; économétrie des données de panel;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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