Abstract
Relative development of Hungarian counties is described generally by the GDP per capita indicator, but this figure does not cover the knowledge gap on the liveability of the regions. The other frequently used method is the indicator systems, but it does not emphasize the structure of causes and consequences of the regional development, and so, it does not provide information on which factors are more likely to be the causes or, reversely, the consequences of the different regional development. To overcome the shortcomings of the above-mentioned methods, we created a structural equation model (SEM) at NUTS 3 level for years 1994–2016 based on the LISREL estimation procedure. The applied model can be classified into experimental statistics, but it uses data only from official statistics, namely the regional indicators published by the Hungarian Central Statistical Office. The model assumes that the economic development depends on observable economic indicators, and it determines the regional development as well. In addition, the regional development is also explained by non-economic, social, demographic and cultural and infrastructural indicators. The variable selection and the classification into causes and consequences was a three-step process, and the factors were classified by analysis of correlations, cross-correlations and Granger-causality. The results of estimation provided basis for a deeper analysis; how the regional development has changed in Hungary after the regime change, and how these variables were influenced by the country’s integration into the global value chain.