A New Method for Measuring the Economic Convergence and Its Application on Central China Provinces

In order to solve the shortcomings of classical convergence analysis and spatial econometric analysis, this paper proposes a delta statistics method to assess economic growth convergence of central China cities. The result shows to be more close to the reality by analyzing the drawbacks of the classical relative beta convergence, combining the advantages of gams convergence, reference panel data, co-integration theory with the time factor into model. Then, Monte Carlo simulation method is used to analyze its distribution, which shows that it obeys to the normal distribution assumption in large samples. At last, our method is applied to the analysis of economic convergence of central China.
Kako bi se otklonili nedostaci klasične analize konvergencije i prostorne ekonometrijske analize, ovaj rad predlaže delta statističku metodu za potrebe procjene konvergencije ekonomskog rasta u gradovima centralne Kine. Rezultati pokazuju da se dolazi bliže stvarnosti analizirajući loše strane klasične relativne beta konvergencije kombinirajući prednosti gama konvergencije, referentnih panelnih podataka, kointegracijske teorije s vremenskim faktorom u modelu. Zatim, Monte Carlo model simulacije se koristi za analizu distribucije što pokazuje da odgovara pretpostavci normalne distribucije u velikim uzorcima. Naposljetku, naša se metoda primjenjuje na analizu ekonomske konvergencije u centralnoj Kini.