2004 Fiscal Year Final Research Report Summary
Non-surveying Construction of a 47 Interregional Input-Output Table and Calibration of SCGE Model
| Project/Area Number |
15560458
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
交通工学・国土計画
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| Research Institution | Gifu University |
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Principal Investigator |
MIYAGI Toshihiko Gifu University, Faculty of Regional Studies, Professor, 地域科学部, 教授 (20092968)
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| Co-Investigator(Kenkyū-buntansha) |
ISHIKAWA Yoshifumi Nanzan University, Faculty of Regional Policy Studies, Associate Professor, 総合政策学部, 助教授 (20329577)
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| Project Period (FY) |
2003 – 2004
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| Keywords | SCGE Model / Inter-regional IO Analysis / Applied General Equilibrium Analysis / 47 Inter-regional IO Table in Japan / Calibration / Interregional Trade Coefficient / Transportation Investment / Chenery-Moses Model |
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| Research Abstract |
Main results of this research ate summarized as follows :
1)Our approach for constructing interregional input-output table is regarded as a hybrid method in which initial trade coefficients estimated by the existing various social-economical data are successively adjusted to satisfy consistency conditions.
2)Our non-surveying technique is based on a balancing-factor method, however, it differs from the conventional balancing-factor method in that our approach should solve linear equation systems for finding one of the balancing-factors.
3)Convergence of the algorithm was successfully examined with usage of small size sample data of Japanese Inter-regional IO data. Application of the algorithm to 47-region data was successfully completed with less than one percentage errors between estimated and actual regional products ; however, for some sectors in several regions, the error exceeds more than ten percentages. Since the amounts of products in such sectors are relatively small, we can expe
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ct that those errors can be reduced by sector aggregation and do not have significant effects on further analysis as well.
4)Constructed interregional input-out table consists of 45 sectors and 47 regions, of which elements account for as much as more than four hundred millions. For finding the Leontief inverse matrix, we have used GAUSS software package. Interdependence analysis is conducted using the 47-interregional table, and we have found interesting results about the economical iuterdependences among metropolitan areas and surrounding regions.
5)We have proposed a new trade model which includes the concept of spatial advantage in terms of economic distance for distinct regions. Spatial advantage are measurable if one can use interregional IO data as the benchmark equilibrium, however, such data are rarely in use in the usual analysis. We have developed the dimension-reduction method in which three-dimensional parameters concerned with spatial advantage is transformed to two-dimensional parameters with assistance of exogenously given parameter on travel times between distinct regions. This method allows us to calibrate trade coefficients without interregional IO data.
6)We have developed and examined several calibration procedures corresponding to the benchmark equilibrium data which are easily obtainable. The worst situation may be the case in which no data except the IO data for total region is available. Even in such a case, our approach can produce satisfactory results in constructing interregional IO estimates. If one can use a complete interregional IO date, the method can reproduce completely consistent estimates with given data by using transformation technique of Chenery-Moses model to Isard type.
From these results, we can conclude that our approach provides a theoretically consistent and practically feasible SCGE model. Unfortunately, however, we could not implement SCGE analysis using the interregional IO data created in this research, mainly due to time limitation and the needs of solving a large scale of nonlinear equation systems. Since this is not an essential problem and merely a technical one, we are optimistic with respect to that. Less
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