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Demographic dynamics and long-run development: insights for the secular stagnation debate

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Abstract

This paper takes a global, long-run perspective on the recent debate about secular stagnation, which has so far mainly focused on the short term. The analysis is motivated by observing the interplay between the economic and demographic transition that has occurred in the developed world over the past 150 years. To the extent that high growth rates in the past have partly been the consequence of singular changes during the economic and demographic transition, growth is likely to become more moderate once the transition is completed. At the same time, a similar transition is on its way in most developing countries, with profound consequences for the development prospects in these countries, but also for global comparative development. The evidence presented here suggests that long-run demographic dynamics have potentially important implications for the prospects of human and physical capital accumulation, the evolution of productivity, and the question of secular stagnation.

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Notes

  1. See Summers (2014) for a detailed account of this view.

  2. See, e.g., the recent book edited by Teulings and Baldwin (2014a), the session on “The Economics of Secular Stagnation” at the Allied Social Science Associations Conference 2015 and activities by the OECD (2015), as well as more formal quantitative work by Eggertsson and Mehrotra (2014).

  3. See, e.g., the discussions in Gordon (2014b) and Mokyr (2014a, b).

  4. The data are extracted from standard publicly available sources. These sources, and the links for the download of the data, are listed in Table 7 in Appendix 1.

  5. We refrain from plotting Asia separately. In terms of income and TFP growth, Asia displays a qualitatively similar pronounced increase after the end of the 1970s, but at higher rates than Africa throughout the observation period.

  6. The question about inefficiently low growth also has a normative component that requires the formulation of an efficient benchmark. The analysis here is deliberately kept positive and avoids normative statements.

  7. Earlier models that feature an endogenous demographic transition following an exogenous decline in mortality include the pioneering work by Ehrlich and Lui (1991). Related work by Becker et al. (1990) predicts nonlinear patterns in fertility, education, and development but does not incorporate the role of mortality. The model considered here has the advantage of providing a parsimonious framework that is able to generate the transition in the different dimensions while lending itself readily to a quantitative simulation in the spirit of unified growth models of the transition from stagnation to growth. This literature originates with the seminal work by Galor and Weil (1999, 2000); see also Galor (2011) for an extensive survey of the unified growth literature. In contrast to the earlier models that feature multiple steady states and the need for exogenous forces to bring about a transition, unified growth models exhibit an endogenous change of the dynamic system that generates the transition, and therefore, provide a more appropriate framework for the purpose of this paper.

  8. Technically, the simulation covers the period 0–2000, but the analysis is conducted over the period 1600–2000.

  9. The baseline model assumes that the extrinsic longevity, the average longevity of an adult who has survived to age 5 without access to any health care or other factors—thus resembling the situation in an entirely undeveloped state of the world—is 45 years. The high mortality scenario corresponds to the same environment, but with an extrinsic longevity of only 40 years. See Cervellati and Sunde (2015a) for the calibration and simulation details.

  10. These predictions are also consistent with the findings by Zhang and Zhang (2005) that life expectancy has a positive but decreasing effect on savings, school enrolment, and growth, as well as a negative effect on fertility.

  11. We take years of schooling and the share of individuals aged 25+ with some formal schooling from Barro and Lee (2010), whereas the human capital index is from the Penn World Table (see Feenstra et al. 2015).

  12. To derive this empirical model, suppose that aggregate income Y is given by a neoclassical production function Y it  = K t γ(A t H δ t ) that uses physical capital K, human capital H, and productivity A, where human capital is given by H it  = e g(hit) L it with h as average years of schooling and where L is the population. Dividing by population and taking logs, one can derive an estimation equation as in (1); for a differenced version, see also Benhabib and Spiegel (1994).

  13. After the demographic transition onset, greater longevity accelerates the expansion of education, thereby reducing fertility and population growth, with positive effects on income per capita. See Cervellati and Sunde (2011a, b, 2015b) for a more structured derivation of these predictions and a more detailed discussion of cohort-specific effects.

  14. The effect of demographic change on savings was at the core of the arguments by Hansen (1939). The nonlinear effect of increases in life expectancy on savings and growth has been predicted in theoretical work, e.g., by Zhang et al. (2003). Lee and Mason (2010) provide a discussion of these issues in the context of global population aging.

  15. The precise relationship between increases in life expectancy and retirement depends on age-specific mortality changes (see D’Albis et al. 2012).

  16. The quantitative version of the unified growth theory presented in Section 3 does not explicitly account for the endogenous evolution of savings, and accordingly physical capital accumulation, during the different development phases. While the theory therefore does not deliver explicit predictions, it is interesting to explore the empirical patterns in light of the focus on interest rates in the secular stagnation debate.

  17. In light of the previous discussion and the fact that education also represents an investment, one might speculate that the distinct roles of life expectancy and old age dependency might also apply to the estimates in Table 1. Table 8 in the Appendix 2 contains corresponding estimates for an extended specification that also controls for the old age dependency ratio. The main finding of a hump-shaped effect of life expectancy on changes in education attainment remains unaffected.

  18. The emphasis on exceedingly low (zero or negative) interest rates in the recent secular stagnation debate is related to the prolonged phase of seemingly ineffective expansionary monetary policy in response to the financial crisis of 2007/8. This aspect of stabilization policy in response to a recession further complicates the picture but goes beyond the long-run perspective taken here. Nevertheless, it should be noticed in this context that the focus on low interest rates was not at the core of the original secular stagnation hypothesis. In fact, Hansen emphasizes the role of population dynamics for output and capital formation, mentioning that “the deepening of capital results partly from cost-reducing changes in technique, partly (though this is probably a much less significant factor) from a reduction in the rate of interest” (Hansen 1939, p. 7).

  19. See Cervellati and Sunde (2016) for a detailed theoretical and empirical analysis of this point.

  20. Life expectancy at the beginning of working age might be more appropriate to conduct this analysis than life expectancy at birth, which contains information on child mortality. We thank a referee for pointing this out.

  21. The results in columns (4) and (6) imply that the quadratic relationship’s minimum is approximately 60 years of life expectancy.

  22. See Table 9 in the Appendix 2 for details.

  23. See Börsch-Supan et al. (2006) for a simulation exercise that illustrates this mechanism.

  24. This depresses the returns on capital and thus real interest rates, in particular if savings are massive due to countries with large populations that face rapidly aging populations, such as China. By themselves, capital flows might affect the development dynamics by interfering with the convergence to the balanced growth path (see, e.g., Birchenall 2007).

  25. For evidence on the distinct role of human capital changes and stocks in terms of growth, see, e.g., Sunde and Vischer (2015).

  26. Zaiceva and Zimmermann (2016) provide a review of the issues related to aging and migration.

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Acknowledgements

The authors wish to thank the editor, Junsen Zhang, as well as three reviewers for helpful comments and suggestions. Thanks also to Lukas Rosenberger for excellent research assistance and to Victoria Finn and Gerrit Meyerheim for editorial comments. Zimmermann gratefully notes support in 2016 as John F. Kennedy Memorial Policy Fellow and Visiting Professor at the Center for European Studies, Harvard University.

Author information

Authors and Affiliations

  1. University of Bologna, Bologna, Italy

    Matteo Cervellati

  2. IZA, Bonn, Germany

    Matteo Cervellati & Uwe Sunde

  3. University of Munich, Munich, Germany

    Uwe Sunde

  4. CEPR, London, UK

    Uwe Sunde & Klaus F. Zimmermann

  5. Princeton University, Princeton, NJ, USA

    Klaus F. Zimmermann

  6. UNU-MERIT, Maastricht, Netherlands

    Klaus F. Zimmermann

Authors
  1. Matteo Cervellati
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  2. Uwe Sunde
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  3. Klaus F. Zimmermann
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Correspondence to Klaus F. Zimmermann.

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Responsible editor: Junsen Zhang

Appendices

Appendix 1. Data sources

Table 7 Data and sources
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Appendix 2. Additional tables

Table 8 Relation between life expectancy and changes in education
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Table 9 Population aging and capital accumulation
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Cervellati, M., Sunde, U. & Zimmermann, K.F. Demographic dynamics and long-run development: insights for the secular stagnation debate. J Popul Econ 30, 401–432 (2017). https://doi.org/10.1007/s00148-016-0626-8

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