Regional well-being in Romania: assessment after a decade of EU accession

Abstract

PurposeThis paper aims to study through a comprehensive set of socioeconomic indicators the regional level of well-being achieved in Romania, and monitor the improvements and disparities in well-being after a decade of accession to the European Union.Design/methodology/approachA dashboard of 20 socioeconomic indicators for measuring nine dimensions of well-being for Romanian counties is proposed. Using the Adjusted Mazziotta-Pareto method are built composite indicators, which allow us to assess the trend of overall welfare scores for each county. The data are collected at the county level, for 42 counties, and each year from 2006 to 2017, from administrative sources.FindingsThe overall well-being index has an increasing trend for all counties, but the growth rate varies from one county to another. The economic factors, geographic location and share of the urban population matter. For most counties, the evolution of well-being scores is below that recorded at the country level. Romania has registered significant improvements in health, housing, income and access to public utilities dimensions. The counties are ranked by level of well-being. Some empirical measures suggest a slight tendency of socioeconomic disparities to increase over time.Originality/valueThe paper attempts to fill some gaps in measuring the level and disparities of welfare in a fast-growing emerging economy. The Romanian regional context is to a lesser extent explored in a multidimensional approach, from spatial and temporal points of view.

Measuring the resilience of rural tourism in Indonesia using the Adjusted Mazziotta-Pareto index

“…Compared with other composite methods, the AMPI has several advantages. These include, among other things, that the AMPI is more robust, it allows space-time comparison among the units being analyzed, and it is less sensitive when one or two indicators are excluded (Mazziotta and Pareto, 2017a;Lazar and Litan, 2022). In addition, the AMPI has a so-called "penalty effect," whereby if a unit in the analysis has a low value in one indicator and a high value in another, then that unit will receive penalty without compensation.…”