Stochastic Dominance Analysis of Income Inequality in the Philippines: 2000-2012

1. Income and Consumption Inequality in the Philippines: A Stochastic Dominance Analysis of Household Unit Records Ma. Rebecca Valenzuela, Monash University, Australia Wing-Keung Wong, Asia University Zhu Zhu Zhen, Lingnan University

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3. Welfare Indicators, Selected Countries, 2000-2012 Source: World Bank. Notes: (i) values over the period averaged by authors from World Bank estimates. (ii) HCR calculated at national poverty lines.

4. Current literature on inequality on the Philippines • all studies use province-level data to measure and assess inequality; • all studies use income data to analyse inequality; none have used expenditure data; and • all of these studies use singular inequality indices.

5. Singular Measures of Inequality • Gini Coefficient • Atkinson Index • Theil index A B Australia 30.2 HK 53.7 Canada 26.1 Sing 46.3 USA 43.0 Ph 44.8

6. What this study does. • Use stochastic dominance approach to analyse inequality in the Philippines, - 2000-2012 unit records - income & consumption data - introduce descending stochastic dominance analysis - apply new tests of richness & poorness

7. Ascending SD Approach Stochastic Dominance Approach income income

8. Descending SD Approach Stochastic Dominance Approach NEW income income

9. What this study does. • Use stochastic dominance approach to analyse inequality in the Philippines, 2000-2012. • introduce descending stochastic dominance (DSD) approach • apply new tests of richness & poorness Ascending Stoch Dom Diminishing marginal utility of income SD Theory Increasing marginal utility of income Descending Stoch Dom

10. Conceptual Framework SWF

11. Ascending Stochastic Dominance FASD means that distribution X will always have less proportion of poor income units than distribution Y for any specified value of x. FASD implies that the expected level of welfare from the F distribution is at least as great as that of G distribution for all increasing welfare functions.

12. Ascending Stochastic Dominance SASD implies that distribution F has a higher expected welfare level than distn Giff SWF is increasing and concave. income

13. Descending Stochastic Dominance FDSD means that distribution X will always have a higher proportion of richer units than distribution Y for any specified value of income x. FDSD implies that the expected level of welfare from the F distribution is at least as great as that of G distribution for all increasing welfare functions.

14. Descending Stochastic Dominance SDSD implies that distribution F has a higher expected welfare level than distribution G for all SWFs increasing and convex. SDSD means that X has more proportion of richer units compared to Y for all sets of incomes at the relatively high levels.

15. Advantages of ASD + DSD Test • First, it allows a more accurate analysis on social welfare - full distribution analysis • allows measure the dominance between two income distributions up to as many income grids as desired • Second, the approach does not require any specific poverty line. • Third, our approach can be used to measure and test for both richness and poorness.

16. The Data • Family Income and Expenditure Survey (FIES) • 2000, 2003, 2006, 2009 and 2012 waves of cross-sectional FIES data covering an average of 39000 households each year. • The household is the basic unit of our analysis • Equivalence scale (SQRT (family size)) • CPI 2006 =100

17. Summary Statistics, FIES 2000 - 2012 • Household coverage was large: 38400 hh(2009) to 42,094 hh(2003). • The share of urban/rural households was steady - 45% U v 55% R percent in the period up to 2009, - 38% U v 62% R percent in 2012 • Wages remain as the main source of income - 45-48% from Wages & Salaries - 34% from Entrepreneurial Activities, down to 27% in 2012 - 20% from Other Sources, increased to 26% in 2012 • Average household size is 4.8. Typical head of household is Male, is between 31 to 60 years old and have completed achieved some high school education at most.

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36. Findings & Conclusions • Welfare levels in 2009 and 2012 actually improved in the economy compared to the early part of this decade. • in the past, wages and salaries households enjoyed highest welfare levels compared to those who depended on entrepreneurial activities or other sources for income. This has however changed in more recent years – we found higher welfare levels amongst those drawing from other sources, which is mainly from remittances. • Results showed increasing concentrations of poor income units amongst the youngest cohort (30 and under), at the same time that there are high concentrations of richer income units in the over60 distributions. • We also found large gaps in relative social well beings across gender and education groups – that is, female-headed households were relatively better off compared to their male-headed counterparts, while higher welfare levels were associated with those who had more years of education.