the notion that measured consumption expenditures are likely to be a better proxy for household income than are measured household incomes (e.g., Deaton and Grosh 2000). This latter measure of sectoral ‘incomes’ is likely to mitigate the underestimation of the level of agricultural income shares as mentioned above. The main assumption in this approach is that sectoral income shares based on wage and enterprise incomes would provide good proxies of the sectoral income shares at the provincial aggregate, a proposition that cannot be verified with existing data. Since there is no a priori reason to believe that either one measure should perform better, this study reports results based on both measures of sectoral incomes and examines the robustness of the results. In addition to the use of two alternative measures of ‘sectoral incomes,’ two separate analyses were conducted on those two measures. First, in an attempt to examine long-run dynamics, the change between 1991 and 2006 is used as the unit of analysis in a crosssection analysis. Second, in order to fully utilize the provincial panel data, all the FIES rounds, conducted every three years between 1991 and 2006, are used as panel data using fixed-effects regression analyses.2 The first sets of results are summarized in Table 7-3. They are based on the regression results replicating equations (5), (7) and (8) of Ravallion and Datt (1996), which investigate the interactions among poverty reduction, sectoral income growth and urbanization (Table 7-3-2, 7-3-3). Unlike what Ravallion and Datt (1996) found in India (where mean income growth in urban areas had no significant impact on national poverty), the mean consumption growth in urban and rural areas are both significantly associated with provincial (both rural and urban areas) poverty reduction. Given the predominance of the rural population (excluding Metro Manila, 66% of the population is found in rural areas on average during the period 19912006), rural growth is relatively more important in reducing provincial poverty incidence than is urban growth. The impact of a one percentage increase in rural growth is found to have at least twice the size of the poverty reduction impact of the same increase in urban growth. In addition, while the coefficients on urbanization (differential population growth rate between urban and rural areas) are negative, suggesting positive effects on poverty reduction, such coefficients are not statistically significantly different from zero. The study also finds that, not surprisingly, rural growth is more important relative to urban growth in reducing rural poverty, while, conversely, urban growth is more important in reducing urban poverty. Again, the coefficients on urbanization, albeit having the expected sign, are not statistically significant in explaining the change in either rural poverty or urban poverty. The much researched ‘Kuznetz effects’ on poverty reduction during the process of economic development, therefore, appear to play a minor role, which is in line with the finding by Ravallion and Datt (1996) in India. The observed relationships between poverty reduction and (urban vs. rural) sectoral growth patterns in the Philippines suggest that stimulating rural growth should be one of the key ingredients for accelerating poverty reduction in rural areas.
2
More detailed information on the regression equations estimated is provided in Annex 7-1 of this chapter.
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