An Economic Wellbeing Index for the Spanish Provinces: A Data Envelopment Analysis Approach

Abstract

data envelopment analysis, economic wellbeing, synthetic index,

How Does Good Governance Relate to Quality of Life?

“…Recent examples are [18] for Italy, [19] for Estonia, and [20] for the Czech Republic. As for Spain, [21][22][23][24][25][26][27][28], have done so for different territories of the country. More recently, González et al [12] and Cárcaba et al [29] have tracked the evolution of municipal QoL in Spain between 2001 and 2011.…”

Assessment of the Tourism’s Potential as a Sustainable Development Instrument in Terms of Annual Stability: Application to Spanish Rural Destinations in Process of Consolidation

“…The aforementioned set of nine variables offers an accurate image of the seasonality in the destinations, since it has an approach consisting of supply, demand and labor market variables and the international component of seasonality. The problem of the degrees of freedom has been solved validating the results obtained introducing a larger number of observations (analyzed destinations) than of variables [98][99][100]118] in the calculation of the DP2. Additionally, this method allows us to identify which variables of the group provide more relevant information to achieve our goal [112].…”

“…Other authors have proposed using Data Envelopment Analysis (DEA) to achieve the same objectives [99,104,105], but this system has several restrictions compared to the DP2, such as the lack of subjectivity in the choice of variables [88]. DEA neither fulfills the principles of uniqueness and monotony in order to preserve variations in changes of origin and/or scale in units of measurement and to consider the interdependence of the indicators [106].…”

“…In addition, by dividing the indicator by a standard deviation, it rules out the problem of heterogeneity in the measurement units of the original indicators, expressing the partial indicators in abstract units [92]. In short, this measure verifies a set of properties, which ensure that the weight of the partial indicators is determined in a non-arbitrary way, and that the weight obtained has an economic interpretation [89,99,101,112,113].…”

“…This indicator solves some common problems such as the heterogeneity of the partial indicators' measurement units, the duplication of information within them and the impact related to each one of them, as guaranteed by the DP2 [10]. One of the improvements provided by this indicator is that it makes the criterion of aggregation of variables expressed in different units unbiased, as well as avoiding arbitrariness when determining the weights of the variables and the duplication of information [93,99]. The entry order of the partial indicators is obtained using the absolute value of the linear correlation coefficients between the values of each indicator and the synthetic indicator [8,100].…”