Regional Economic Effects of CO₂ Reduction Activities with Wood Biomass: Application and Extension of a Regional IO Model

Abstract

In order to reduce greenhouse gas (GHG) emissions interest in green energy such as biomass, wind mills and solar electric generation is growing. In a regional economic context, numerous local municipalities in Japan are attempting to reduce CO₂ emissions by making use of regional environmental resources such as wood (forest) , wind and sunlight (solar) . Some municipalities export as well as intraregional usage as an alternative of oil resources. These municipalities usually estimate how much CO₂ can be reduced by their environmental activities. However, the economic impacts of such efforts are ambiguous.
Representative policies for correcting regional income disparities so far include income transfers, plant location as related to outside areas and public investment. These policies, however, depend on national policies. In this study, we focused on regional environmental resources, particularly wood biomass, and examined economic effects of the utilization of such regional environmental resources by applying an extended regional I-O analysis.
To do so, we first constructed two types of I-O tables at the prefecture level and city/town level by making use of survey methods to obtain import/export data. Next, we reconstructed regional I-O tables by focusing on wood biomass and CO₂ credit service sectors to evaluate the economic effects of wood biomass and exporting credit. We defined economic effects of introducing renewable energy as three kinds: intraregional circulation effects as energy alternatives, export effects and supply cost effects. Transduction to biomass energy from oil induces changes in the structure of the input-output linkage. After conducting several simulations including changes in I-O structure, we found that the use of wood biomass contributes to an increase in regional per capita income if trading carbon offset credit is institutionalized. This effect is more significant at the city/town level than prefecture level.

JEL Classification: C67, Q57, R11, R15