1. 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. 2 Large deficits at young and old ages. Reallocations from surplus to deficit ages required.

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. 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. 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. 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.

9. 9

10. 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. 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. 12 Tradeoff between HK and TFR: International Cross-section Source: Lee and Mason, forthcoming, European Journal of Population. Estimated elasticity of HK/W per child wrt TFR is -1.05.

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

14. 14 Public consumption

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

16. 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. 17 Labor Income as a Source of Funding Consumption for 65+ (Above Average)

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

19. 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. 20 The First Demographic Dividend First Demographic Dividend

21. 21 Economic Support Ratio Kenya 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. 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. 23 Dividends: Medium scenario, tau = 0.35 2 nd dividend weak in simulation because of low consumption among elderly.

24. 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. 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. 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. 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 Lee, Ronald (ronlee), Co-Directorronlee Mason, Andrew (amason), Co-Directoramason Auerbach, Alan (auerbach)auerbach Miller, Tim (tmiller)tmiller Lee, Sang-Hyop (leesang)leesang Donehower, Gretchen (gstockma)gstockma Ebenstein, Avi (ebenstei)ebenstei Wongkaren, Turro (turro)turro Takayesu, Ann (takayesa)takayesa Boe, Carl (cboe)cboe Comelatto, Pablo (pabloc)pabloc Sumida, Comfort (comfort)comfort Schiff, Eric (eric)eric Stojanovic, Diana (diana)diana Langer, Ellen (erlanger)erlanger Chawla, Amonthep (beet) Pajaron, Marjorie Cinco (pajaron)pajaron

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

29. 29 Australia Key Institution: Australia National University Jeromey Temple, Country Leader Brazil Turra, Cassio(cturra), Country Leadercturra Lanza Queiroz, Bernardo(lanza)lanza Renteria, Elisenda Perez(elisenda)elisenda Chile Key Institution: United Nations Economic Commission for Latin America and the Carribean, Santiago, Chile Bravo, Jorge(jbravo2), Country Leaderjbravo2 China Key Institution: China Center for Economic Research, Beijing, China. Ling, Li(Lingli), Country LeaderLingli Chen, Quilin(Chen)Chen

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

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

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

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

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

35. 35 INTRODUCING African Country TeamsCOUNTRYTEAM Kenya Germano Mwabu Moses Muriithi Reuben Mutegi Mozambique Gilberto Norte Ramos Muanamoha Nigeria Adedoyin Soyibo Akanni Lawanson Olanrewaju Olaniyan Senegal Latif Dramani Fahd Ndiaye Ouarme Alaya South Africa Haroon Bhorat Morne Oosthuizen Toughedah Jacobs

36. 36 The End