Abstract
Management of the old industrial regions’ development is a very actual problem, in particular for the post-Soviet countries. It is connected with the fact that the purposes of manufacture modernization which provide employment and incomes of the population of such regions, can contradict requirements of environmental protection. Here the most different scenarios of development are possible which need to be evaluated. Usual neoclassical criteria for this purpose do not match. Therefore, in our paper, there was a task to develop such criterion which can be used for regulation of the old industrial regions’ development taking into account the environmental factor. The paper begins with construction of regional economy model. Our model based on the J. Forrester's “world model” idea, i.e. it considers the influence of environmental pollution (atmosphere, water, earth) on the population disease level, and then—on the lifetime and the human capital; the latter ones are considered as one of the most important factors of the economic growth. On the ground of this model, the consequences for realization of different scenarios of the regional economy development are estimated. To substantiate the regulation of regional economy, the criterion of sustainable development, based on the idea of simultaneous improvement of economic and ecological parameters, is offered. The main feature of the criterion offered is that, first of all, it guarantees simultaneous improvement of each of the chosen indicators of the region’s development, and, second, allows considering interests of various coalition groups by finding realistic compromises at a choice of ways of old industrial regions’ development.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Usually the labour, earth, capital and entrepreneurship are considered as the factors of the economic growth. The ecology is not included here. But it is obvious that it influences the specified resources of the industrial activity; it means that it is also a factor but only of the second level. All of these factors’ joint influence on the economic growth is investigated in the article. The task of evaluation of separate factors’ influence in this case is not considered.
The model offered, basically, can be used for any type of the region development analysis, but in a considerable degree it is used for the old industrial regions where the tendency to deterioration of the ecological situation has a strongly pronounced character.
To simplify the model only the fixed assets (buildings and equipment) are considered, taking into account that there is enough current capital, given by the financial system.
The problems of aggregation in production functions is discussed in (Felipe and Fisher 2003). We assumed that capital is enterprises’ buildings and equipment and CES is engineering production functions. This type of production function describes "… the maximum level of output that can be achieved if the inputs were efficiently employed" (Felipe and Fisher 2003, p. 5).
Values of other indicators are given in Table 1.
The increase in the value of goods and services, produced in a country (GDP), can be considered as potential Pareto-improvement, which means that the gains of one or more economic agents in principle can set off losses of others and to raise the total welfare. Although, as is known, GDP is not the absolute index of welfare because the latter depends on estimating externalities, leisure time etc. Moreover, "… there is no such thing as a single, and satisfactory, measure of economic welfare; only a set of complementary variables, one of which could be GDP, has the potential for conveying an adequate sense of a country's economic welfare; and there is no such thing as an entirely objective set of complementary variables; some cannot be estimated in monetary terms and subjective factors cannot be eliminated" (Tarasofsky 1998).
Optimization was made in Powersim with genetic algorithms. It is caused by difficulties of applying the classical methods of the nonlinear functions optimization, related to the local extremes problems and calculations time growth with the problem increase. Genetic algorithms allow overcoming the mentioned questions by "cultivation" of the optimum decision by crossing the initial variants with the subsequent selection by some criteria.
Horizon periods are used only to find an optimum value \( k_{I}^{e} \). The duration of the forecast period is identical for all alternate designs and it makes 25 years. For example, if n 1 = 10, the found optimum value of investments distribution factor between investments in the fixed assets and environmental funds is \( k_{I}^{e} \; = \;0.0026 \) and this value is used for calculating indicators for all 25 years, as shown in Fig. 2.
Pareto choice multicriterion problem on the final set of known alternatives is usually solved by consecutive application of tabular methods and the hierarchy analysis. This also permits to avoid the discrepancy of the private criteria. However, this tool in our case is not suitable, as there is no a priori given set of region’s development alternatives (except two extreme variants for which the Pareto set area is empty), and we form it ourselves by the proposed criterion by varying indicators \( T_{i}^{Y} \) and \( T_{i}^{d} \).
To be convinced that value i, which was obtained following the results of optimization with sustainable development criterion, is too minimum, special calculation has been made for i → min.
References
Felipe, J., & Fisher, F. (2003). Aggregation in production functions: What applied economists should know. Metroeconomica, 54(2–3), 208–262.
Forrester, J. W. (1968). Principles of systems. Portland, Oregon: Productivity Press.
Forrester, J. W. (1969). Urban dynamics. Portland, Oregon: Productivity Press.
Forrester, J. W. (1970). World dynamics. Portland, Oregon: Productivity Press.
Forrester, J. W. (2007). System dynamics—a personal view of the first fifty years. System Dynamics Review, 23(2–3), 345–358.
Gowdy, J. (2004). The revolution in welfare economics and its implications for environmental valuation and policy. Land Economics, 80(2), 239–257.
Leontief, V., & Ford, D. (1972). Air pollution and the economic structure: Empirical results of input-output computations. In A. Brody & A. P. Carter (Eds.), Input-output techniques: Papers presented at the fifth international conference on input-output techniques, Geneva, January, 1971. Amsterdam: North-Holland Publishing Company.
Levenberg, K. (1944). A method for the solution of certain non-linear problems in least squares. The Quarterly of Applied Mathematics, 2, 164–168.
Meadows, D. H., Meadows, D. L., & Randers, J. (1992). Beyond the limits: Confronting global collapse, envisioning a sustainable future. Post Mills, Vermont: Chelsea Green.
Meadows, D. H., Meadows, D. L., Randers, J., & Behrens, W. W., III (1972). The limits to growth: A report for the club of Rome’s project on the predicament of mankind. New York: Universe Books.
Moiseev, N., Alexandrov, V., Krapivin, V., Lotov, A., Svirezhev, Y., Tarko, A. (1983). Global models, the biospheric approach: Theory of the Noosphere. IIASA 1983 CP-83-33, 1–50.
Tarasofsky, A. (1998). GDP and its derivatives as welfare measure: A selective look at the literature (pp. 1–2). Ottawa, Ontario: Centre for the Study of Living Standards.
United Nations Development Programme (UNDP) (2009). Human Development Report 2009. Overcoming barriers: Human mobility and development. Retrieved from http://hdr.undp.org/en/media/HDR_2009_EN_Complete.pdf. Accessed 21 Dec 2009.
Author information
Authors and Affiliations
Corresponding author
Additional information
Readers should send their comments on this paper to BhaskarNath@aol.com within 3 months of publication of this issue.
Rights and permissions
About this article
Cite this article
Vishnevsky, V., Aleksandrov, I. & Polovyan, A. Scenarios of the old industrial regions’ development: selecting the methodology. Environ Dev Sustain 13, 65–78 (2011). https://doi.org/10.1007/s10668-010-9248-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10668-010-9248-6