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Aging and Savings in Korea: A Time-Series Approach

Abstract

Thanks to numerous empirical research studies, a general consensus has been reached on the effects of an aging population on the economy, particularly in terms of economic growth and savings. However, most of the previous research examines the effects of the aging on economically advanced countries. Furthermore, rarely have those studies used the time-series properties of the data. By applying two popular time-series statistical tools (multivariate cointegration analysis and vector error correction model) to Korean data, this paper finds: (1) There is a long-run equilibrium linkage among the aging, medical expenditure and savings; however (2) there is no Granger-causality present between aging and national savings in the short run in Korea.

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References

  1. Alessie, R.; Lusardi, A.; Kapteyn, A. “Saving After Retirement: Evidence from Three Different Surveys,” Labour Economics, 6 (2), June, 1999, pp. 277–310.

  2. Boersch-Supan, A. H.; Winter, J. K. “Population Aging, Savings Behavior and Capital Markets,” NBER Working Papers: 8561, National Bureau of Economic Research, Inc., 2001.

  3. Cantor, R.; Yuengert, A. “The Baby Boom Generation and Aggregate Savings,” Quarterly Review-Federal Reserve Bank of New York, 19 (2), Summer-Fall, 1994, pp. 76–91.

  4. Dickey, D. A.; Fuller, W. A. “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root,” Econometrica, 49 (4), June, 1981, pp. 1057–72.

  5. Enders, W. RATS Handbook for Econometric Time Series, Wiley, 1996, pp. 177–88.

  6. Futagami, K.; Nakajima, T. “Population Aging and Economic Growth,” Journal of Macroeconomics, 23 (1), Winter, 2001, pp. 31–44.

  7. Granger, C. W. J. “Investigating Causal Relationships by Econometric Models and Cross Spectral Models,” Econometrica, 37 (3), July, 1969, pp. 424–38.

  8. Heller, P. S.; Symansky S. “Implications for Savings of Aging in the Asian ‘Tigers’,” Asian Economic Journal, 12 (3), September, 1998, pp. 219–52.

  9. Horioka, C. Y. “A Cointegration Analysis of the Impact of the Age Structure of the Population on the Household Saving Rate in Japan,” The Review of Economics and Statistics, 79 (3), August, 1997, pp. 511–16.

  10. Johansen, S. “Statistical Analysis of Cointegration Vectors,” Journal of Economic Dynamics and Control, 12 (2/3), June/September, 1988, pp. 231–54.

  11. Johansen, S.; Juselius, K. “Maximum Likelihood Estimation and Inference on Cointegration – With Applications to the Demand for Money,” Oxford Bulletin of Economics and Statistics, 52 (2), May, 1990, pp. 169–210.

  12. Korea National Statistical Office. World and Korea Population Status, 2002.

  13. —. World and Korea Population Status, 2005.

  14. Kwon, Soonman. “Fiscal Crisis of the National Health Insurance in Korea: In Search of a New Paradigm,” International Symposium on Health Care Systems in Asia, Hitotsubashi University, Japan, January 2005.

  15. Modigliani, F. “The Life Cycle Hypothesis of Saving and Intercountry Differences in the Saving Ratio,” In: Eltis, W. A., Scott, M. F. G., Wolfe, J. N. Induction, Growth and Trade: Essays in Honour of Sir Roy Harrod, London: Clarendon, 1970, pp. 197–225.

  16. Palumbo, M. G. “Uncertain Medical Expenses and Precautionary Saving Near the End of the Life Cycle,” Review of Economic Studies, 66 (2), April, 1999, pp. 395–421.

  17. Sabelhaus, J. “Public Policy and Saving in the United States and Canada,” Canadian Journal of Economics, 30 (2), May, 1997, pp. 253–75.

  18. White, H. “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity,” Econometrica, 48 (4), May, 1980, pp. 817–38.

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Correspondence to Doh-Khul Kim.

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Kim, D., Kim, H. Aging and Savings in Korea: A Time-Series Approach. Int Adv Econ Res 12, 374–381 (2006). https://doi.org/10.1007/s11294-006-9024-4

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Keywords

  • Aging
  • Savings
  • Cointegration Test
  • VECM
  • Granger-causality

JEL

  • D12
  • J14