Identyfikacja klastrów w oparciu o strukturę nakładów i wyników

Henryk Gurgul, Paweł Majdosz

Gurgul, Henryk
Majdosz, Paweł
Identyfikacja klastrów w oparciu o strukturę nakładów i wyników
Input-Output Table Based Method of Cluster Identification
Zeszyty Naukowe SGGW - Ekonomika i Organizacja Gospodarki Żywnościowej, 2006, vol., nr 60, s. 103-112

Słowa kluczowe

Model nakładów i wyników klastry metoda triangulizacji

Key words

Input-output model clusters triangulization method

Streszczenie

W artykule tym omówiono najczęściej stosowane w praktyce metody identyfikowania klastrów na podstawie tablic input-output oraz zaproponowano metodę triangulizacji, która umożliwia wykrywanie powiązań istniejących między dobrze zdefiniowanymi klastrami lub między sektorami należącymi do klastrów i spoza nich. Zastosowanie metody triangulizacji zilustrowano na przykładzie tablic przepływów międzygałęziowych dla polskiej gospodarki w 2000 roku w agregacji 55 x 55 sektorów

Abstract

An idea beyond the triangulization method is that an intermediate demand should be categorized as an intra-cluster if it is large enough not only from economy-wide perspective. Also it should be considered as a significant one by both buyer and seller. Doing so, the triangulization method provides a better insight into the actual structure of economy by distinguishing between three types of links, namely intra-cluster flows, flows which take place between two sectors belonging to different clusters, and flows from sector within cluster to sector outside of clusters. It turned out that the triangulization method leads to the solution which is, at least, as good as those of the diagonalization method. In addition, the solution obtained by using this method is irrespective of applying the intermediate demand matrix, input coefficient matrix, or output coefficient matrix. On the other hand, when applying the Leontief inverse, the identified clusters are different compared to those in the case where we used one of the above-mentioned matrices. It is worth noting that clusters seem to be a quite important in the Polish economy. The sectors belonging to the clusters created approximately a 70 per cent of gross output in 2000, and a 60 per cent of value added, final consumption expenditures, import and export in the same year. However, this conclusion should be drawn with care due to the fact that the high aggregation (55 x 55 sectors) was used in this study. Therefore, this part of our investigation should be repeated in the future at low level of data aggregation as far as possible.