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The main problems of constructing multiregional input-output (IO) models used for the development of spatial and sectoral long-term national economy forecasts are caused by the absence of proper statistics. Therefore, it is necessary to make up the input-output tables (IOTs) based on a limited set of direct and indirect indicators that measure spatial patterns of production, consumption, capital formation, etc., sufficiently accurate for filling up multiregional IO models. The paper discusses Russian IOT spatial mapping problems and proposes an approach to partial automation of the procedures necessary for regional IOT construction (by federal districts). The regionalization was carried out using a static IO model with the bounding sum control. As a result, a set of consistent regional tables for 2015 was developed, with the eight IOT sum equalling Russia's IOT. Based on the estimated regional IOTs, a static multiregional input-output model (OMIOM) across federal districts for 2015 was made up. The model allows us to proceed to the follow-up phase, i. e., developing a semi-dynamic model for long-term national economic projection computations

1. Introduction -- 1.1. Objectives and Scope of the Study -- 1.2. Plan of the Study -- 2. Input—Output Models with a Regional Dimension -- 2.1. Introduction -- 2.2. The National Input—Output Model -- 2.3. The Interregional Input—Output Model -- 2.4. Multiregional Input—Output Models -- 2.5. Choice of the Model for Long-Run Simulation -- 2.6. Summary -- 3. The MRIO Model in Long-Run Simulation -- 3.1. Introduction -- 3.2. Problems with MRIO Long-Run Simulation -- 3.3. Revising Interregional Trade Patterns -- 3.4. A Potential Inconsistency in MRIO -- 3.5. Summary and Introduction to the Remaining Chapters -- 4. The Extended MRIO Price Model -- 4.1. Introduction -- 4.2. Input—Output Price Models Again -- 4.3. The Extended IRIO Price Model -- 4.4. A Nonsurvey Method of Extension -- 4.5. Some Other Practical Problems -- 4.6. The Extended MRIO Price Model -- 4.7. Summary -- 5. Multinomial Logit Models of Trade Coefficients -- 5.1. Introduction -- 5.2. Estimating Trade Patterns Again -- 5.3. The Discrete Choice Model -- 5.4. The Diversification Benefit Model -- 5.5. Some Comparisons -- 5.6. Summary -- 6. Linking the Trade Coefficient Model to the Price Model -- 6.1. Introduction -- 6.2. The Price Model Consistent with the Discrete Choice Model -- 6.3. The Price Model Consistent with the Diversification Benefit Model -- 6.4. Equilibrium Solutions -- 6.5. Lagged Solutions in Simulation -- 6.6. Summary -- 7. An Interregional Simulation Model for Indonesia -- 7.1. Introduction -- 7.2. The Model Structure -- 7.3. Summary -- 8. Testing the MNL Trade Coefficient Models Using Indonesian Data -- 8.1. Objective and Approach -- 8.2. Models To Be Estimated -- 8.3. Data -- 8.4. Results -- 8.5. Summary -- 9. Towards Long-Run Simulation Modeling with an MRIO Model -- 9.1. Introduction -- 9.2. Remaining Issues -- 9.3. Concluding Remarks -- Appendix 2. Derivation of the Mean and Standard Deviation of the Weibull Distribution -- Appendix 3. Cost Calculation of Transport Subsectors -- Appendix 4. Background of the Indonesian Modeling Exercise -- Appendix 5. The Data Set -- References -- Author Index.

The note presents the computation of industry foreign inputs dependency using input-output tables. It gives details on each level of dependency and finish with the infinite computation using the Leontief inverse matrix. It ends with some evidence by using WIOT data from 2000 to 2014 which shows the high growth of the technical dependency to Chinese inputs over the past 15 years. Construction, Telecommunications and Chemicals are Chinese-dependent sectors among the 20 first which also contribute a lot to the French economy. Nevertheless, for France and European countries, the dependency to Chinese inputs is well behind the dependency to European inputs.

The note presents the computation of industry foreign inputs dependency using input-output tables. It gives details on each level of dependency and finish with the infinite computation using the Leontief inverse matrix. It ends with some evidence by using WIOT data from 2000 to 2014 which shows the high growth of the technical dependency to Chinese inputs over the past 15 years. Construction, Telecommunications and Chemicals are Chinese-dependent sectors among the 20 first which also contribute a lot to the French economy. Nevertheless, for France and European countries, the dependency to Chinese inputs is well behind the dependency to European inputs.