Production Networks and Spatial Economic Interdependence: An International Input-Output Analysis of the Asia-Pacific Region

The Asia-Pacific Region has enjoyed remarkable economic growth in the last three decades. This rapid economic growth can be partially attributed to the global spread of production networks, which has brought about major changes in spatial interdependence among economies within the region. By applying an Input-Output based spatial decomposition technique to the Asian International Input-Output Tables for 1985 and 2000, this paper not only analyzes the intrinsic mechanism of spatial economic interdependence, but also shows how value added, employment and CO2 emissions induced are distributed within the international production networks.

Spatial patterns of manufacturing clusters in Vietnam

The formation of industrial clusters is critical for sustained economic growth. We identify the manufacturing clusters in Vietnam, using the Mori and Smith (2013) method, which indicates the spatial pattern of industrial agglomerations using the global extent (GE) and local density (LD) indices. Spatial pattern identification is extremely helpful because industrial clusters are often spread over a wide geographical area and the GE and LD indices—along with cluster mapping—display how the respective clusters fit into specific spatial patterns.

Spatial structures of manufacturing clusters in Cambodia, Lao People's Democratic Republic, and Thailand

Examining the spatial structure of clusters is essential for deriving regional development policy implications. In this study, we identify the manufacturing clusters in Cambodia, the Lao People's Democratic Republic, and Thailand, using two indices—global extent (GE) and local density (LD)—as proposed by Mori and Smith (2013). We also analyze four different combinations of these indices to highlight the spatial structures of industrial agglomerations. Since industrial clusters often spread over administrative boundaries, the GE and LD indices—along with cluster mapping—display how the detected clusters fit into specific spatial structures.