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Robustness in regional development studies. The case of Lithuania


  • Willem Karel M. Brauers
  • Romualdas Ginevičius


The definition of robustness in econometrics, the error term in a linear equation, was not only broadened, but, in addition, moved to the meaning of common language: from a cardinal to a qualitative one: the most robust one, more robust than…, as robust as……, robust, weak robust, less robust than…, not robust, etc. Both interpretations are tested by an application on the Robustness in Regional Development, namely of the Lithuanian Regions. The computation of Regional Income, being an exponent of the welfare economy, is not sufficient for the measurement of the well‐being of the regional population. The well‐being economy goes farther. In the well‐being economy, each individual would have to feel good concerning material wealth, health, education, all kind of security and concerning the environment. In other words, multiple objectives have to be fulfilled. Moreover, these different multiple objectives are expressed in different units. Weights are most of the time used to equalize these different units. However, introduction of weights means also introduction of subjectivity. In order to avoid this dilemma, the internal mechanical solution of a ratio system, producing dimensionless numbers, is preferred. In addition, this outcome creates the opportunity to use also a non‐subjective reference point theory. The choice of the objectives is also non‐subjective if all stakeholders are involved, or if all possible objectives are represented. This theory, which is called MOORA (Multi‐Objective Optimization by Ratio Analysis), is applied to the different regions of Lithuania. A redistribution of income has to take place from the well‐being Lithuanian regions to the poorer regions, but under limiting conditions and for well defined and eventually controlled projects.

Suggested Citation

  • Willem Karel M. Brauers & Romualdas Ginevičius, 2009. "Robustness in regional development studies. The case of Lithuania," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(2), pages 121-140, February.
  • Handle: RePEc:taf:jbemgt:v:10:y:2009:i:2:p:121-140
    DOI: 10.3846/1611-1699.2009.10.121-140

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    References listed on IDEAS

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    Cited by:

    1. Willem K. M. Brauers, 2012. "Project Management for a Country with Multiple Objectives," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 6(1), pages 80-101, March.
    2. Romualdas Ginevičius & Dainora Gedvilaite & Šarunas Bruzge, 2015. "Assessment of a Country’s Regional Economic Development on the Basis of Estimation of a Single Process (ESP) Method," Entrepreneurial Business and Economics Review, Centre for Strategic and International Entrepreneurship at the Cracow University of Economics., vol. 3(2), pages 141-153.
    3. repec:ers:journl:v:vi:y:2018:i:2:p:68-82 is not listed on IDEAS
    4. Gülçin Canbulut & Erkan Köse & Oğuzhan Ahmet Arik, 2022. "Public transportation vehicle selection by the grey relational analysis method," Public Transport, Springer, vol. 14(2), pages 367-384, June.
    5. Nilsen Kundakcı, 2016. "Combined Multi-Criteria Decision Making Approach Based on MACBETH and MULTI-MOORA Methods," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(1), pages 17-26, April.
    6. R.G. Akhmadeev & O.A. Bykanova & N.V. Philippova & I.V. Vashchekina & T.B. Turishcheva, 2018. "Macroeconomic Indicators and their Impact on the Foreign Debt Burden: The Case of BRICS Countries," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 68-82.

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