Improvement of financial autonomy of the rural municipalities in Lithuania using the spatial modelling method

Abstract

In the scientific literature, the financial autonomy (FA) of rural municipalities has been referred to as a complex and dynamic phenomenon. Its manifestation has been claimed to depend on a variety of externalities and internalities of the local government. Rural municipalities occupy a significant share of the geographical space of the European Union and are very diverse. Hence, the manifestation of autonomy of the local government and possibilities for improvement of the FA in the rural areas are specific for each country and are characterised by their diversity and complexity. The issue of improvement of the FA has become of particularly topical interest in the context of regional and rural development in recent years. It has become increasingly relevant in autonomous and sustainable decision-making and implementation by the local governments as well as in the search for sustainable financial resources in spatial terms. Research aim: to develop the recommendations on improvement of the FA of the rural municipalities in Lithuania in the context of the key endogenous factors identified. The article presents the empirical research findings obtained as a result of an assessment of the FA of 36 rural municipalities in Lithuania under the multi-criteria decision analysis method TOPSIS. The restraining and driving endogenous factors of the FA of the rural municipalities were analysed by applying the Moran’s I statistic method. Global Moran’s I statistic and Cluster and Outlier Analysis (Anselin Local Moran's I) were used to check for global and local patterns in the distribution of the FA of Lithuanian municipalities and related factors. The research findings have demonstrated low or medium low the FA of rural municipalities in Lithuania. The result has been determined by the rapidly deteriorating demographic situation, restraining social factors, and contrasting economic environment observed in rural areas of Lithuania during the recent 11 years. The spatial autocorrelation models enabled the identification of the rural municipality clusters characterized by insufficient economic development and concentrated in the western and southern regions of the country. The spatial modelling-based assessment of the endogenous factors and using the tree-based regression model technique has shown the possibilities for improvement of the FA of rural municipalities of Lithuania. JEL Classification H72, R11, R15.