Applications of National Transfer Accounts (NTA) in Research and Policy Making

1. Applications of National Transfer Accounts (NTA) in Research and Policy Making Sang-Hyop Lee, East-West Center & University of Hawaii Presented to the Workshop on “Shaping Social Protection in Africa: the NTA Approach” May 13-27, 2009 Mombasa, Kenya

2. Reallocations from surplus to deficit ages required. Large deficits at young and old ages.

3. 3 Population Age Distributions

4. Aggregate Lifecycle • Based on per capita profile for developing countries weighted by UN estimates of 2005 age structure. • Two features are of interest • Overall dependency: Total difference between labor income and consumption. • Direction of IG flows: Do flows to children or the elderly dominate?

5. Research Questions about the Economic Lifecycle • Will change in age structure lead to demographic dividend? • Are the dividends sustainable? • What policies are needed? • Will fertility decline lead to a decline in spending on children and, in particular, their human capital? • Quantity-quality tradeoff: Becker • Political economy arguments: Preston • Can the finance of health care and long term care be improved? • Can policies raise the labor production by the elderly? • Age at retirement: Gruber and Wise • Productivity of older workers:

6. Other Sources of Funding Consumption (Reallocation System) • Familial Transfers • Asset-based Reallocations • Interest, dividends, rent from personal assets • Home and other consumer durables • Dis-saving • Public Transfers • Social Security System

7. Research Questions about the Reallocation Systems • How do reallocation systems vary across countries and over time? • What is the impact of policies that expand or contract public transfers to the elderly? • Crowd out private transfers? If so, does this effect fertility? • Crowd out saving and thereby reduce economic growth? • Can we “stress test” reallocation systems?

8. The NTA Projects… • Develop a system of economic accounts that can be used to study the macroeconomic implications of change in age structure. • Estimate the accounts with historical depth for economies with different cultures, levels of development, economic systems and policies. • Analyze and explain • variation in the economic lifecycle and the reallocation systems, • macroeconomic effects of population aging, • economic implications of pension, health care, education, child subsidies, and other policy. • Led by Ron Lee and Andrew Mason. • Currently 24 country teams are participating.

10. Important Features of the NTA • Comprehensive approach: • All mechanisms for shifting resources from one age group to another are incorporated into the accounts. • Both public and private institutions are incorporated. The role of the family is emphasized. • NTA is consistent with and complementary to National Income and Product Accounts.

11. Evidence to present • Consumption by children • Lee and Mason: HK tradeoff curve. • Ogawa et al.: Spending on children in Taiwan and Japan • Consumption profiles for the elderly • Labor income of elderly • Participation • Productivity • Reallocation system (simulation)

12. Tradeoff between HK and TFR: International Cross-section Estimated elasticity of HK/W per child wrt TFR is -1.05. Source: Lee and Mason, forthcoming, European Journal of Population.

13. Consumption: Industrialized vs. Developing Countries. More on elderly (health care) More on education

14. 1.2 1 Japan 2004 0.8 US 2003 Uruguay 94 Thailand 04 Philippine 99 Mexico 04 Normalized (30-49 labor income) 0.6 Indonesia 02 Hungary 05 Finland 04 Costa Rica 04 Chile 97 0.4 Taiwan 03 0.2 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Age Public consumption

15. Labor Income: Industrialized vs. Developing Countries More on children More on elderly

16. Kenya: High Participation, Low Productivity for Children and Elderly Implication: Due to high participation, delaying retirement has little effect on elderly labor income.

17. Labor Income as a Source of Funding Consumption for 65+ (Above Average)

18. Labor Income as a Source of Funding Consumption for 65+ (Below Average)

19. Research Questions about the Reallocation Systems • How do reallocation systems vary across countries and over time? • What is the impact of policies that expand or contract public transfers to the elderly? • Crowd out private transfers? If so, does this effect fertility? • Crowd out saving and thereby reduce economic growth? • Can we “stress test” reallocation systems?

20. The First Demographic Dividend First Demographic Dividend

21. Economic Support RatioKenya 1950-2050 Noted: Scenarios based on most recent UN Projections; In 2050 TFR for low scenario is 1.9, for medium scenario is 2.4, and for high scenario is 2.9.

22. The Second Demographic Dividend • Population aging can lead to an accumulation of wealth to meet pension needs for retirement. • If workers save more (relying on asset-based reallocations) in anticipation of aging, higher income is possible even after the first dividend period has come to an end. • Alternatively, workers can rely on transfer wealth (PAYGO pension programs, familial transfer), which has little effect on growth (in our model, we assume that the % of transfer wealth is fixed).

23. Dividends: Medium scenario, tau = 0.35 2nd dividend weak in simulation because of low consumption among elderly.

24. Some Remarks • The gains from relying heavily on asset-based reallocations are realized in the form of higher assets with small gains in consumption. • Later in the simulation (not shown), gains in consumption are substantially higher with smaller reliance on transfer programs to support the elderly. • For example, using the medium scenario per capita consumption is higher in 2100 by 14% for tau=0.35 than tau=0.6.

25. Policy Implications • Good policies • that are consistent with poverty reduction goals • that do NOT undermine work and saving incentives, and promote growth • and that are financially sustainable. • One set of policy implications are • economic policy that can best accommodate population policy • Influencing population change and age structure, per se.

26. Conclusions • Population matters • Population size and age structure • Policy matters • Implication for growth; but underdeveloped financial markets may limit investment opportunities. • Early policy response is essential to realize the demographic dividend. • The NTA provides a research tool. • Economic lifecycle • Reallocation system

27. The National Transfer Accounts project is a collaborative effort of East-West Center, Honolulu and Center for the Economics and Demography of Aging, University of California - Berkeley

28. Taiwan Key Institution: The Institute of Economics, Academia Sinica, Taipei, Taiwan. Tung, An-Chi(actung), Country Leader Lai, Mun Sim (Nicole)(munsim) Liu, Paul K.C.(kliu) Andrew Mason Japan Key Institutions: Nihon University Population Research Institute and the Statistics Bureau of Japan, Tokyo, Japan. Ogawa, Naohiro(ogawa), Country Leader Matsukura, Rikiya(matukura) Fukui, Takehiro(jstat) Kondo, Makoto(kondo) Akasaka, Katsuya(akasaka) Nemoto, Kazuro(nemoto) Makabe, Naomi(makabe) Sato, Ryoko(rsato) Ogawa, Maki(mogawa) Murai, Minako(murai) Obayashi, Senichi(obayashi) Suzuki, Kosuke(Suzuki)

29. Australia Key Institution: Australia National University Jeromey Temple, Country Leader Brazil Turra, Cassio(cturra), Country Leader Lanza Queiroz, Bernardo(lanza) Renteria, Elisenda Perez(elisenda) Chile Key Institution: United Nations Economic Commission for Latin America and the Carribean, Santiago, Chile Bravo, Jorge(jbravo2), Country Leader China Key Institution: China Center for Economic Research, Beijing, China. Ling, Li(Lingli), Country Leader Chen, Quilin(Chen)

30. France Wolff, Francois-Charles(wolff), Country Leader Bommier, Antoine(bommier) Thailand Key Institution: Economics Department, Thammasat University. Phananiramai, Mathana(Mathana), Country Leader Chawla, Amonthep (Beet)(amonthep) Inthornon, Suntichai(Suntichai) India Key Institution: Institute for Social and Economic Change, Bangalore Narayana, M.R.(narayana), Country Leader Nanak Kakwani(kakwani) Ladusingh, L.(ladusingh) Mexico Key Institution: Consejo Nacional de Población Partida, Virgilio (virgilio), Country Leader Mejía-Guevara, Iván(ivan)

31. Indonesia Key Institution: Lembaga Demografi, University of Indonesia, Jakarta, Indonesia. Maliki(maliki), Country Leader Wiyono, Nur Hadi(nhwiyono) Nazara, Suahasil(nazara) Chotib(chotib) Philippines Key Institution: Philippine Institute for Development Studies. Racelis, Rachel H.(Rachel), Country Leader Salas, John Michael Ian S.(Salas) Sweden Key Institution: Institute for Future Studies, Stockholm, Sweden. Lindh, Thomas(lindh), Country Leader Johansson, Mats(Mats) Forsell, Charlotte (charlotte)

32. Uruguay Bucheli, Marisa(marisa), Country Leader Furtado, Magdalena(furtado) South Korea An, Chong-Bum (cban) Lee, Sang-Hyop (leesang) Chun, Young-Jun (yjchun) Gim, Eul-Sik (kuspia)

33. Austria Key Institution: Vienna Institute of Demography Fuernkranz-Prskawetz, Alexia (alexia), Country Leader Sambt, Joze(joze) Costa Rica Key Institution: CCP, Universidad de Costa Rica Rosero-Bixby, Luis(lrosero), Country Leader Slovenia Sambt, Joze(joze), Country Leader

34. United States Key Institution: Center for the Economics and Demography of Aging Lee, Ronald(ronlee), Country Leader Miller, Tim(tmiller) Ebenstein, Avi(ebenstei) Boe, Carl(cboe) Comelatto, Pablo(pabloc) Donehower, Gretchen(gstockma) Schiff, Eric(eric) Langer, Ellen(erlanger)

35. INTRODUCING African Country Teams

36. The End