Abstract
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. First Publish Online: 09 Jun 2011
Highlights
The error term in a linear equation is the starting point for the definition of robustness in econometrics (Darnell 1997: 355)
The method taking into consideration consumer sovereignty is more robust than this one which does not respect consumer sovereignty; 2) the method of multiple objectives in which all non-correlated objectives are considered is more robust than this one in which only a limited number of objectives is considered; 3) the method of multiple objectives in which all interrelations between objectives and alternatives are taken into consideration at the same time is more robust than this one in which the interrelations are only examined two by two; 4) the method of multiple objectives which doesn’t need external normalization is more robust than this one which needs a subjective external normalization
The method of multiple objectives with inside normalization through the non-subjective dimensionless measures is more robust than this one which uses subjective weights or subjective non-additive scores like in the traditional reference point theory (Brauers and Zavadskas 2008: 168–170; Brauers 2004: 158–159); 5) the method of multiple objectives based on cardinal numbers is more robust than this one based on ordinal numbers:“an ordinal number is one that indicates order or position in a series, like first, second, etc.” (Kendall and Gibbons 1990)
Summary
The error term in a linear equation is the starting point for the definition of robustness in econometrics (Darnell 1997: 355). From the beginning Bayesian analysis has to be characterized as cardinal, with a high grade of arbitrariness This arbitrariness could be softened by considerations on robustness. Kreps (1990) maintains that more robustness is more important for bargaining theory than for auction theory as more information is available in the latter case than in the former. If robustness is indicated as vague or arbitrary is it not the case with inference statistics (Hoel 1971 versus Hays 1974), probability theory (Hays 1974) and statistical specification H. 1970: 312)? Third, robustness is characterized by completeness being present in the statistical population, when defined as covering events and opinions which are present, as well as in the statistical universe with events and opinions present and possible
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