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Accounting for Heterogeneity in Growth Incidence in Cameroon Using Recentered Influence Function Regression

Author

Listed:
  • B. Essama-Nssah

    (Independent Consultant (Former World Bank Senior Economist))

  • Paul Saumik

    (Osaka University)

  • Léandre Bassolé

    (African Development Bank)

Abstract

This paper frames growth incidence analysis within the logic of social impact evaluation understood as an assessment of variations in individual and social outcomes attributable to shocks and policies. It uses recentered influence function (RIF) regression to link the growth incidence curve (GIC) to household characteristics and perform counterfactual decomposition à la Oaxaca-Blinder to identify sources of variation in the distribution of consumption expenditure in Cameroon in 2001-2007. We find that the structural effect is driven mostly by the sector of employment and geography and is the main driver of the observed pattern of growth. The composition effect accounts for the lion’s share of the observed variation in the social impact of growth. In particular, that effect tends to reduce poverty while the structural effect tends to increase it. This conclusion is robust with respect to the choice of poverty measures and RIF regression models.

Suggested Citation

  • B. Essama-Nssah & Paul Saumik & Léandre Bassolé, 2013. "Accounting for Heterogeneity in Growth Incidence in Cameroon Using Recentered Influence Function Regression," Working Papers 288, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2013-288
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    References listed on IDEAS

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    Cited by:

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    2. Ferreira,Francisco H. G. & Firpo,Sergio & Galvao,Antonio F., 2017. "Estimation and inference for actual and counterfactual growth incidence curves," Policy Research Working Paper Series 7933, The World Bank.
    3. Livini Donath & Oliver Morrissey & Trudy Owens, 2021. "Pay period and the distributional effect of education on earnings: Evidence from recentered influence function," Discussion Papers 2021-02, University of Nottingham, CREDIT.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O55 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Africa
    • 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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