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

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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

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Reallocations from surplus to deficit ages
required.
Large deficits at young and old ages.
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3 Population Age Distributions
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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?

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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

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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

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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?

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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.

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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.

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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)

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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.
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Consumption Industrialized vs. Developing
Countries.
More on elderly (health care)
More on education
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Public consumption
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Labor Income Industrialized vs. Developing
Countries
More on children
More on elderly
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Kenya High Participation, Low Productivity for
Children and Elderly
Implication Due to high participation, delaying
retirement has little effect on elderly labor
income.
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Labor Income as a Source of Funding Consumption
for 65 (Above Average)
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Labor Income as a Source of Funding Consumption
for 65 (Below Average)
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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?

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The First Demographic Dividend
First Demographic Dividend
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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.
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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).

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Dividends Medium scenario, tau 0.35
2nd dividend weak in simulation because of low
consumption among elderly.
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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 tau0.35
  than tau0.6.

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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.

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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

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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-Director Mason, Andrew (amason), Co-Director Auerbach, Alan (auerbach) Miller, Tim (tmiller) Lee, Sang-Hyop (leesang) Donehower, Gretchen (gstockma) Ebenstein, Avi (ebenstei) Wongkaren, Turro (turro) Takayesu, Ann (takayesa) Boe, Carl (cboe) Comelatto, Pablo (pabloc) Sumida, Comfort (comfort) Schiff, Eric (eric) Stojanovic, Diana (diana) Langer, Ellen (erlanger) Chawla, Amonthep (beet) Pajaron, Marjorie Cinco (pajaron)
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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)
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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)
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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)
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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)
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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)
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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
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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)
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INTRODUCING African Country Teams
COUNTRY TEAM
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
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The End