3 resultados para Spatial Point Pattern analysis
em Academic Research Repository at Institute of Developing Economies
Resumo:
This paper proposes an alternative input-output based spatial-structural decomposition analysis to elucidate the role of domestic-regional heterogeneity and interregional spillover effects in determining China's regional CO2 emission growth. Our empirical results based on the 2007 and 2010 Chinese interregional input-output tables show that the changes in most regions' final demand scale, final expenditure structure and export scale give positive spatial spillover effects on other regions' CO2 emission growth, the changes in most regions' consumption and export preference help the reduction of other regions' CO2 emissions, the changes in production technology, and investment preference may give positive or negative impacts on other region's CO2 emission growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emission growth. All these facts can significantly help better and deeper understanding on the driving forces of China's regional CO2 emission growth, thus can enrich the policy implication concerning a narrow definition of "carbon leakage" through domestic-interregional trade, and relevant political consensus about the responsibility sharing between developed and developing regions inside China.
Resumo:
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.
Resumo:
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.