Microsimulations of Poverty and Inequality Using the Distribution of Welfare

  • Federico Perali


Recent research suggests that income growth is effective in reducing poverty and does not have a negative impact on income distribution. Rather, the unequal distribution of income and assets can be an impediment to rapid growth (Bourguignon, de Melo and Morrisson 1991, Deininger and Squire 1997). Poverty and inequality seem to be closely related to the economic cycle, rising during a period of recession, falling during recovery and staying the same during a stagnant phase. As the evidence presented in this chapter shows, these stylized facts are further supported by the Colombian experience during the second half of the 1980s.


Poverty Line Capita Expenditure Gini Coefficient Equivalence Scale Poverty Measure 
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  1. 1.
    The macroeconomic figures are taken from the International Monetary Fund, International Financial Statistics, World Bank data and the 1998–1999 Report on the Economic and Social Progress in Latin America, Inter-American Development Bank.Google Scholar
  2. 2.
    To this purpose, we refer the interested reader to the works of Esteban and Ray 1994, Duclos and Grégoire 1999, Chakravarty 2002, Cowell and Ebert 2002, Decoster and Ooghe 2002, Duclos, Esteban and Ray 2002, Foster, Shneyerov and Slotsve 2002.Google Scholar
  3. 3.
    Gustafsson (1995) distinguishes between endogenous and exogenous poverty lines. Endogenous poverty lines are those constructed from the analyzed data only. Exogenous poverty lines are those constructed from other sources. For example, in the case of an endogenous poverty line defined as one half of mean income, the poverty line for a transformed distribution is simply one half of the mean of adjusted income. This is not the case of Colombia, where the poverty line is constructed from the cost of acquiring a basic food basket (See also note 5).Google Scholar
  4. 4.
    For simplicity, the first two moments of the distribution are assumed sufficient to fully characterize its properties. Both the original and the transformed expenditure distributions considered in the analysis are log-normal according to the results of the KolmogorovSmirnov and Skewness-Kurtosis tests. However, the more is learned about the shape and the statistical properties of the expenditure distribution, the higher is the precision of the transformation.Google Scholar
  5. 5.
    The method implemented by Munoz used the same Encuesta de Ingresos y Gastos 198485 to estimate (1) the normative food basket that a) satisfies the minimal nutritional protein and calory requirements, b) accounts for the food habits of the population, c) minimizes the costs, and (2) the poverty line corresponding to the indigence line, the cost of acquiring the basic food basket estimated at 3,000 pesos per capita, times a coefficient equal to the ratio between total expenditure and total food expenditure in the low income households.Google Scholar
  6. 6.
    Note that the figures report the logarithmic transformations of the expenditure series while the tables report expenditures and welfare at their original levels.Google Scholar
  7. 7.
    The poverty estimates are comparable with the estimates obtained by the World Bank Country Study of Poverty in Colombia (1994) using different data sets. As an example, see Figure 1.1 on page 3 or Table 1.5 on page 201 of Annex 1 where the estimates of poverty incidence are computed with respect to the poverty rather than the indigence line. Another reference for comparison are the studies by Cardenas and Gutierrez (1997) and Londono de la Cuesta (1997).Google Scholar
  8. 8.
    The estimated Gini coefficients are comparable with the estimates obtained by the World Bank Country Study (1994) for Colombia using other national household surveys as shown by the estimates reported in Table 1.11 of Annex 1 at page 209. Another reference showing the stability of the inequality indicators during the period 1985–1990 is Londono de la Cuesta (1997).Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • Federico Perali
    • 1
    • 2
  1. 1.University of VeronaItaly
  2. 2.CHILD (Center for Household, Income, Labour, and Demographics)Italy

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