Skip to main content
Log in

Modeling Regional Disparities for a Balanced Quality of life and Apportioning Public Funding – a Graph Theoretical Approach

  • Published:
Applied Research in Quality of Life Aims and scope Submit manuscript

Abstract

Inclusive and equitable development is imperative in today’s society as persistence of regional disparities may create social discontentment. Public spending is largely responsible for equitable development in different regions under common governance. This study attempts to analyze the regional disparities by studying the data of an Indian state and model these in terms of district development digraph with a focus to highlight the methodology for apportioning development funds for minimizing regional imbalances. The nodes in the digraph represent the development variables and the edges represent the degree of influence among these. An equivalent matrix representation of the digraph is developed to define the district development function (DDF). Disparity Index (DI) is defined in terms of DDF and is used to apportion public spending to facilitate equitable growth.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. District is an administrative sub-division of a state in India.

  2. Kumbh Mela: It is a religious festival of Hindus wherein they take dip in the holy river Ganges to wash away their sins – this coincides with the ingress of planet Jupiter in the Aquarius sign

  3. Pucca road is a local term derived from Hindi language and refers to roads that are designed to be solid and permanent. The term is applied for roads or houses in South Asia that are built using material such as stone, coal tar, brick, cement or concrete

References

  • Aggarwal, J. C., Agrawal, S. P., & Gupta, S. S. (Eds.). (1995). Uttarakhand: past, present, and future. New Delhi: Concept Publishing Co.

    Google Scholar 

  • Asadullah, M. N., & Yalonetzky, G. (2012). Inequality of educational opportunity in India: changes over time and across states. World Development, 40(6), 1151–1163.

    Article  Google Scholar 

  • Barua, A., & Chakraborty, P. (2010). Does Openness Affect Regional Inequality? A Case Study for India. Review of Development Economics, 14(3), 447–465.

    Article  Google Scholar 

  • Bhattacharya, N., & Mahalanobis, B. (1967). Regional disparities in household consumption in India. Journal of the American Statistical Association, 62(317), 143–161.

    Article  Google Scholar 

  • Capuno, J. J. (2012). Agglomeration and sub-regional disparities under decentralization: Evidence of spatial clustering of land values in Philippines. Review of Urban and Regional Development Studies, 24(3), 106–120.

    Article  Google Scholar 

  • Chan, K. W. (1996). Post-Mao China: a two class urban society in the making. International Journal of Urban and Regional Research, 20(1), 134–150.

    Article  Google Scholar 

  • Cox, A. T., & Followill, R. A. (2012). The equitable financing of growth: A proportionate share methodology for calculating development impact fees. The Engineering Economist, 57(3), 141–156.

    Article  Google Scholar 

  • Darvish, M., Yasaei, M., & Saeedi, A. (2009). Application of the graph theory and matrix methods to contractor ranking. International Journal of Project Management, 27(6), 610–619.

    Article  Google Scholar 

  • Das, S. K., & Barua, A. (1996). Regional inequalities, economic growth and liberalization: A study of the Indian economy. The Journal of Development Studies, 32(3), 364–90.

    Article  Google Scholar 

  • Deo, N. (1974). Graph Theory. Englewood Cliffs, New Jersey, USA: Prentice Hall.

    Google Scholar 

  • Donkor, E. A., & Duffey, M. (2013). Optimal capital structure and financial risk of project finance investments: A simulation optimization model with chance constraints. The Engineering Economist, 58(1), 19–34.

    Article  Google Scholar 

  • Fan, C. C. (1997). Uneven development and beyond: regional development theory in post-Mao China. International Journal of Urban and Regional Research, 21(4), 620–639.

    Article  Google Scholar 

  • Firman, T. (2009). Decentralization reform and local-government proliferation in Indonesia: Towards a fragmentation of regional development. Review of Urban and Regional Development Studies, 21(2–3), 143–157.

    Article  Google Scholar 

  • Fischer, D. W. (1970). The relevance of benefit cost analysis for economic development. The Engineering Economist, 15(2), 63–80.

    Article  Google Scholar 

  • Gillanders, R. (2013). Corruption and infrastructure at the country and regional level. The Journal of Development Studies. doi:10.1080/00220388.2013.858126.

    Google Scholar 

  • Gregory, D., Johnston, R., Pratt, G., Watts, M., & Whatmore, S. (Eds.). (2009). Quality of Life. Dictionary of Human Geography (5th ed.). Oxford, UK: Wiley-Blackwell.

    Google Scholar 

  • Gupta, P., Gupta, S., & Gandhi, O. P. (2013). Modeling and evaluation of MTTR at product design stage based on contextual criteria. Journal of Engineering Design, 24(7), 499–523.

    Article  Google Scholar 

  • Hseih, C.-M., & Kenagy, G. P. (2014). Measuring quality of life: A case for re-examining the assessment of domain importance weighting. Applied Research in Quality of Life, 9(1), 63–77.

    Article  Google Scholar 

  • Jurkat, W. B., & Ryser, H. J. (1966). Matrix factorization of determinants and permanents. Journal of Algebra, 3(1), 1–27.

    Article  Google Scholar 

  • Kahneman, D., & Deaton, A. (2010). High income improves evaluation of life but not emotional well-being. Proceedings of the National Academy of Sciences, 107(38), 16489–16493.

    Article  Google Scholar 

  • Kar, S. (2007). Institute of Economic Growth Working Paper, E/281/2007. New-Delhi: India. Inclusive Growth in Hilly Regions: Priorities for the Uttarakhand Economy.

    Google Scholar 

  • Kreyszig, E. (1983). Advanced Engineering Mathematics. USA: John Wiley and Sons Inc.

    Google Scholar 

  • Krimi, M. S., Yusop, Z., & Hook, L. S. (2010). Regional development disparities in Malaysia. Journal of American Science, 6(3), 70–78.

    Google Scholar 

  • Le Gallo, J., & Ertur, C. (2003). Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe, 1980–1995. Papers in Regional Science, 82(2), 175–201.

    Article  Google Scholar 

  • Mogha, S. K., Yadav, S. P. and Singh, S. P. (2013) New slack model based efficiency assessment of public sector hospitals of Uttarakhand: State of India. International Journal of System Assurance Engineering and Management. http://dx.doi.org/10.1007/s.13198-013-0207-0.

  • Neves, P. C., & Tavares Silva, S. M. (2014). Inequality and growth: Uncovering the main conclusions from the empirics. The Journal of Development Studies, 50(1), 1–21.

    Article  Google Scholar 

  • Poteete, A. R. (2009). Is development path dependent or political? A reinterpretation of mineral-dependent development in Botswana. The Journal of Development Studie, 45(4), 544–571.

    Article  Google Scholar 

  • Sakamoto, H., & Fan, J. (2013). Regional income disparity in China using value added data: Decomposition and distribution dynamics. Review of Urban and Regional Development Studies, 25(1), 16–33.

    Article  Google Scholar 

  • Samli, A. C. (2008). Entrepreneurship economic development and quality of life in third-world countries. Applied Research in Quality of Life, 3(3), 203–213.

    Article  Google Scholar 

  • Singh, N., Bhandari, L., Chen, A., & Khare, A. (2002). Regional inequality in India: A fresh look. UC Santa Cruz Economics Working Paper, 532, 2–23.

    Google Scholar 

  • Spahr, R. W., Huseynou, F., & Jain, P. (2012). Governement as the firm’s third financial stakeholder: Impact on capital investment decisions, capital structure, discount rates and valuation. The Engineering Economist, 57(3), 157–177.

    Article  Google Scholar 

  • Su, H-T and Tung, Y-K ((2012) Minimax expected opportunity loss: A new criterion for risk-based decision making. The Engineering Economist, 57 (4), 247–273.

  • Tripathi, S. (2013). Do large agglomerations lead to economic growth? Evidence from urban India. Review of Urban and Regional Development Studies, 25(3), 176–200.

    Article  Google Scholar 

  • Vázquez, S. T., & Sumner, A. (2013). Revisiting the meaning of development: A multidimensional taxonomy of developing countries. The Journal of Development Studies, 49(12), 1728–1745.

    Article  Google Scholar 

  • Younsi, M., & Chakroun, M. (2014). Inequality and social heterogeneity in self reported health status in the Tunisian population – An analysis using MIMIC model. Applied Research in Quality of Life, 9(1), 79–97.

    Article  Google Scholar 

Download references

Acknowledgement

The author is thankful to officials in the various departments of the Government of Uttarakhand, India for providing data to carry out this work. The author gratefully acknowledges the motivation provided by Prof. Amitabh Kundu, JNU, New Delhi, India and Prof. V.K. Jain, Vice-Chancellor, Doon University, Dehradun, India to carry out this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shalini Gupta.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gupta, S. Modeling Regional Disparities for a Balanced Quality of life and Apportioning Public Funding – a Graph Theoretical Approach. Applied Research Quality Life 10, 473–493 (2015). https://doi.org/10.1007/s11482-014-9327-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11482-014-9327-1

Keywords

Navigation