1. Working Group: National Transfer Accounts for Population Subgroups Cássio M. Turra & Maurício Holz Seventh Global Conference of the NTA Network East-West Center, Hawaii, June 2010

2. Main Motivations The NTA project has examined how resources are allocated in the life cycle by comparing mean flows across age groups  However, compositional effects may affect the estimation of mean flows  Also, mean flows by age may cover different patterns of intergenerational allocations within each country

3. Central Question Are we interested in a cross-sectional analysis (incidence, progressiveness), in a life cycle analysis (net transfers by SES at birth) or in both?

4. Research questions for the cross-sectional (period) analysis 1.What is the incidence of public and private transfers by population subgroups? 2.How much different are NTA mean flows by age groups from NTA weighted mean flows by age groups?

5. Research questions for the cross-sectional (period) analysis 3.How progressive are taxes and spending (net public transfers) by age groups? Should we also look at distributional measures for private transfers? 4.What are the roles played by unit costs of providing public transfers and the use of these services in the incidence and progressiveness analyses?

6. 1) Incidence of public and private transfers (Turra and Queiroz 2006)

7. 1) Incidence of public and private transfers (Lee and Miller 2007)

8. 1) Incidence of public and private transfers (Turra, Holz and Cotlear 2010)

9. 2) Mean flows vs. weighed mean flows Aggregating unit costs may mask real economic age profiles The unit costs for certain types of public transfers may vary by income groups, geographic regions and races For example, in Brazil, (types and costs) of public health services my differ between high and low income groups, residents in the SE and NE, blacks and whites Of course, this discussion is over when we are able to estimate individual values in the micro-data(e.g. pensions)

10. 2) Mean flows vs. weighed mean flows (Lionel Demery)

11. 3) Progressiveness of public and private transfers Several progressivity measures are available for public transfers: –transfers as a % of income or expenditures –Lorenz curves –Index of progressivity (based on Lorenz curves) –Linear regression analysis (spending on income quintile as a function of income quintile) Estimate progressivity measures by large age groups and types of public transfers? Should we also use distributional measures for private transfers?

12. 3) Progressiveness of transfers (Roach 2003)

13. 3) Progressiveness of transfers (Breceda et al. 2009)

14. 4) Decomposing the flows by unit costs and utilization rates (PT xi /N xi )= (PT xi / B xi ) x (B xi / N xi ) Should we simulate the effect of changing units costs or utilization rates on incidence and progressivity?

15. 4) Decomposing the flows by unit costs and utilization rates (Turra, Holz and Cotlear 2010)

16. Other issues for the cross-sectional (period) analysis  What are the best SES measures to use (not a big issue in the period analysis)?  Individual behavior is not considered (we need to be careful with counterfactual analysis)  Average benefit vs. marginal benefit  We should avoid any life cycle implications from period estimates

17. Research questions for the life-cycle (cohort) analysis 1.What are the Net Present Value of public transfers for population sub-groups? Are there any transfers between population subgroups over the life cycle? 2.Integrate period and life cycle estimates (Lee 2000)

18. Lee and Miller (2007)

19. Life Cycle + Period estimates Zorzin, Wajnman and Turra, following Lee(2000) MenWomen Life Cycle Ratio 1.101.41 Period Ratio 0.941.10

20. Main issues for the life cycle (cohort) analysis  What are the best SES measures to use?  How biased would be the estimates based on a hypothetical cohort (period) data?  Should we include transition rates among SES (from birth to death) in the calculation of NPVs?