Skip to main content
SpringerLink
Log in

Sustainability and intertemporal equity: a multicriteria approach

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

In (macro)economics literature, the need to consider sustainability and intertemporal equity issues leads to propose different criteria (discounted utilitarianism, green golden rule, Chichilnisky criterion) in order to define social welfare. We compare and assess the outcomes associated to such alternative criteria in a simple macroeconomic model with natural resources and environmental concern (Chichilnisky et al. in Econ Lett 49:174–179, 1995), by relying on a multicriteria approach. We show that among these three criteria, the green golden rule (discounted utilitarianism) yields the highest (lowest) welfare level, while the Chichilnisky criterion leads to an intermediate welfare level which turns out to be increasing in the weight attached to the asymptotic utility. These results suggest that completely neglecting finite-time utilities and focusing only on the asymptotic utility is not only more sensible from a sustainability point of view but also from a social welfare maximization standpoint.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Another critical aspect associated to the use of the utilitarian approach is related to the role of the population size and its eventual growth. Specifically, two different utilitarian approaches have been proposed in literature, the average (welfare coincides with individual or average utility) and total (welfare is the sum of individual utilities across the population) utilitarianism. See Palivos and Yip (1993) or more recently Marsiglio and La Torre (2012), Boucekkine and Fabbri (2013), and Marsiglio (2014) for a discussion of the implications of different utilitarian approaches. Since we abstract from population growth and normalize the population size, in our paper average and total utilitarianism coincide, thus we do not explicitly relate to this branch of the literature.

  2. Several other criteria have been proposed in literature but to a large extent they turn out to be ad hoc proposal or do not allow a direct comparison with discounted utilitarianism (Pezzey 1997; Arrow et al. 2004; Marsiglio 2011).

  3. Another interesting related work is Le Kama’s (2001), showing that by choosing the green golden rule utility level as Ramsey’s bliss point for the non-discounted problem the optimal utilitarian path converges to the green golden rule outcome.

  4. The scalarization and the GP approach coincide when the objectives values of the GP are chosen exactly equal to each objective taken singularly. When we introduce the preferences via the satisfaction function the outcome of the two approaches is generally different and the similarities occurring in our results are given by the above mentioned matching of the GP objectives with each objective taken singularly.

References

  • André, F. J., Cardenete, M. A., & Romero, C. (2009). A goal programming approach for a joint design of macroeconomic and environmental policies: A methodological proposal and an application to the Spanish economy. Environmental Management, 43, 888–898.

    Article  Google Scholar 

  • Aouni, B., & Kettani, O. (2001). Goal programming model: A glorious history and a promising future. European Journal of Operational Research, 133, 225–231.

    Article  Google Scholar 

  • Aouni, B., Colapinto, C., & La Torre, D. (2013). A cardinality constrained stochastic goal programming model with satisfaction functions for venture capital investment decision making. Annals of Operations Research, 205, 77–88.

    Article  Google Scholar 

  • Aouni, B., & La Torre, D. (2010). A generalized stochastic goal programming model. Applied Mathematics and Computation, 215, 4347–4357.

    Article  Google Scholar 

  • Aouni, A., Ben Abdelaziz, F., & La Torre, D. (2012a). The stochastic goal programming model: Theory and applications. Journal of Multicriteria Decision Analysis, 19, 185–200.

    Article  Google Scholar 

  • Aouni, B., Colapinto, C., & La Torre, D. (2012b). Stochastic goal programming model and satisfaction function for media selection and planning problem. International Journal of Multicriteria Decision Making, 2, 391–407.

    Article  Google Scholar 

  • Arrow, K., Dasgupta, P., Goulder, L., Daily, G., Ehrlich, P., Heal, G., et al. (2004). Are we consuming too much? Journal of Economic Perspectives, 18, 147–172.

    Article  Google Scholar 

  • Barro, R. J., & Sala-i-Martin, X. (2004). Economic growth. Cambridge, MA: MIT Press.

    Google Scholar 

  • Boucekkine, R., & Fabbri, G. (2013). Assessing Parfit’s repugnant conclusion within a canonical endogenous growth set-up. Journal of Population Economics, 26, 751–767.

    Article  Google Scholar 

  • Charnes, A., & Cooper, W. W. (1959). Chance-constrained programming. Management Science, 6, 73–80.

    Article  Google Scholar 

  • Charnes, A., & Cooper, W. W. (1968). Deterministic equivalents for optimising and satisfying under chance constraints. Operations Research, 11, 11–39.

    Google Scholar 

  • Charnes, A., Cooper, W. W., & Ferguson, R. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1, 138–151.

    Article  Google Scholar 

  • Chinchilnisky, G., Heal, G., & Beltratti, A. (1995). The green golden rule. Economics Letters, 49, 174–179.

    Google Scholar 

  • Chinchilnisky, G. (1997). What is sustainable development? Land Economics, 73, 476–491.

    Google Scholar 

  • Eliasson, L., & Turnovsky, S. J. (2004). Renewable resources in an endogenously growing economy: Balanced growth and transitional dynamics. Journal of Environmental Economics and Management, 48, 1018–1049.

    Article  Google Scholar 

  • Figuieres, C., & Tidball, M. (2012). Sustainable exploitation of a natural resource: A satisfying use of Chichilnisky’s criterion. Economic Theory, 49, 243–265.

    Article  Google Scholar 

  • Gamper, C. D., & Turcanu, C. (2007). On the governmental use of multi-criteria analysis. Ecological Economics, 62, 298–307.

    Article  Google Scholar 

  • Guitouni, A., & Martel, J. M. (1998). Tentative guidelines to help choosing an appropriate MCDA method. European Journal of Operational Research, 109, 501–521.

    Article  Google Scholar 

  • Heal, G. (2005). Intertemporal welfare economics and the environment. In K. G. Maler & J. R. Vincent (Eds.), Handbook of environmental economics (Vol. 3). Amsterdam: North-Holland.

    Google Scholar 

  • Hwang, C. L., & Masud, A. S. (1979). Multiple objective decision making, methods and applications: A state-of-the-art survey. Berlin: Springer.

    Book  Google Scholar 

  • Janssen, R. (2001). On the use of multi-criteria analysis in environmental impact assessment in the Netherlands. Journal of Multicriteria Decision Analysis, 10, 101–109.

    Article  Google Scholar 

  • Le Kama, A. D. A. (2001). Sustainable growth, renewable resources and pollution. Journal of Economic Dynamics & Control, 25, 1911–1918.

    Article  Google Scholar 

  • Marsiglio, S. (2011). On the relationship between population change and sustainable development. Research in Economics, 65, 353–364.

    Article  Google Scholar 

  • Marsiglio, S. (2014). Reassessing Edgeworth’s conjecture when population dynamics is stochastic. Journal of Macroeconomics, 42, 130–140.

    Article  Google Scholar 

  • Marsiglio, S., & La Torre, D. (2012). Population dynamics and utilitarian criteria in the Lucas–Uzawa model. Economic Modelling, 29, 1197–1204.

    Article  Google Scholar 

  • Martel, J. M., & Aouni, B. (1990). Incorporating the decision-maker’s preferences in the goal-programming model. Journal of the Operational Research Society, 41, 1121–1132.

    Article  Google Scholar 

  • Mohtadi, H. (1996). Environment, growth, and optimal policy design. Journal of Public Economics, 63, 119–140.

    Article  Google Scholar 

  • Nijkamp, P., & van Delft, A. (1977). Multicriteria analysis and regional decisionmaking. Boston: Kluwer Nijhoff.

    Google Scholar 

  • Palivos, T., & Yip, C. K. (1993). Optimal population size and endogenous growth. Economics Letters, 41, 107–110.

    Article  Google Scholar 

  • Pezzey, J. C. V. (1997). Sustainability constraints versus “optimality” versus intertemporal concern, and axioms versus data. Land Economics, 73, 448–466.

    Article  Google Scholar 

  • Ramsey, F. (1928). A mathematical theory of saving. Economic Journal, 38, 543–559.

    Google Scholar 

  • Sawaragi, Y., Nakayama, H., & Tanino, T. (1985). Theory of multiobjective optimization. Orlando: Academic Press.

    Google Scholar 

  • Shmelev, S. E. (2011). Dynamic sustainability assessment: The case of Russia in the period of transition (1985–2007). Ecological Economics, 70, 2039–2049.

    Article  Google Scholar 

  • Steuer, R. E. (1986). Multiple criteria optimization: Theory, computation, and application. New York: Wiley.

    Google Scholar 

  • von Weizsäcker, C. C. (1967). Lemmas for a theory of approximately optimal growth. Review of Economic Studies, 34, 143–151.

  • World Commission on Environment and Development. (1987). Our common future. Oxford: Oxford University Press.

Download references

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Management, Ca’ Foscari University of Venice, Venice, Italy

    Cinzia Colapinto

  2. Department of Economics, Management and Quantitative Methods, University of Milan, Milan, Italy

    Danilo Liuzzi

  3. School of Accounting, Economics and Finance, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia

    Simone Marsiglio

Authors
  1. Cinzia Colapinto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Danilo Liuzzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Simone Marsiglio
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Simone Marsiglio.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Colapinto, C., Liuzzi, D. & Marsiglio, S. Sustainability and intertemporal equity: a multicriteria approach. Ann Oper Res 251, 271–284 (2017). https://doi.org/10.1007/s10479-015-1837-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-015-1837-1

Keywords

Search

Navigation