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We make the case for a technology-enabled approach to Smart Specialisation policy making in order to foster its effectiveness by proposing a novel type of economic impact assessment. We use the RHOMOLO model to gauge empirically the general equilibrium effects implied by the Smart Specialisation logic of intervention as foreseen by the policy makers designing and implementing the European Cohesion policy. More specifically, we simulate the macroeconomic effects of achieving the R&D personnel targets planned by a set of Southern European regions. We discuss the implications of the proposed methodology for future assessments of Smart Specialisation.

In response to the 2008/2009 global financial crisis (GFC), many developing countries, including Indonesia, launched fiscal stimulus packages (FSP). These FSPs typically consist of several sophisticated fiscal policies that may not necessarily complement each other. While the impact of these policies at the aggregate country level in developed countries has been widely discussed, the spatial impact of these policies within developing countries is less understood. Utilizing an inter-regional computable general equilibrium (CGE) model, this paper aims to assess and understand the short- and long-term economic impacts of these stimulus policies using Indonesia as a case study. This paper, hence, provides a quantitative ex-post assessment of FSPs typically implemented during the 2009 GFC by developing economies. Overall, results, indicate that fiscal stimulus had a positive impact on aggregate demand and on poverty prevention, principally via stimulating private consumption. Corporate income tax cuts have the largest economic impact in the long-run, and cash transfers are the most useful policy tool for alleviating poverty. An FSP, however, could have an uneven spatial distributional effect on output across regions, particularly in the short-term.

We present an analysis on cohesion policy investments in the regions of Romania using the spatial dynamic general equilibrium model RHOMOLO in order to provide useful insights on the 2021-2027 programmes and their implications for growth and development. The analysis is based on a hypothetical distribution of the funding across the following fields of intervention: aid to the private sector, research and development, transport infrastructure, other infrastructure, and human capital. These interventions are modelled using a mix of demand and supply side shocks. We find that a projected €31.3 billion of cohesion policy funding would increase Romanian GDP by 3.8% at the end of the 10-years implementation period with respect to the no policy scenario. Our results suggest that there seems to be an equity-efficiency trade-off in Romania: in most cases, the returns of the policy in terms of GDP are maximised by investing in the capital city region, at the expense of worsening regional disparities. For some fields of intervention, though, the spillovers generated in the less developed regions are so large that the national GDP impact is similar when investing there rather than in the capital city region.

We analyse the general equilibrium effects of an asymmetric decrease in transport costs, combining a large scale spatial dynamic general equilibrium model for 267 European NUTS 2 regions with a detailed transport model at the level of individual road segments. As a case study we consider the impact of the road infrastructure investments in Central and Eastern Europe in the context of the EU cohesion policy programme. Our analysis suggests that the decrease in transportation costs benefits the regions targeted by the policy via substantial increases in GDP and exports compared to the baseline, and small increases in population. The geographic information embedded in the transport model leads to relatively large predicted benefits in peripheral countries such as Greece and Finland who hardly receive funds, but whose trade links cross Central and Eastern Europe and thus profit from the investments there. The richer, Western European non-targeted regions also enjoy a higher GDP after the investment in the East, but these effects are smaller. Thus, the policy reduces interregional disparities. There are rippled patterns in the predicted spillovers of the policy. In non-targeted countries, regions trading more intensely with regions where the investment is taking place on average benefit more compared to other regions within the same country, but also compared to neighbouring regions across an international border. Using regression analysis we uncover that regions which import intermediate inputs from Central and Eastern Europe enjoy the largest spillovers. These regions become more competitive and expand exports locally, at the detriment of other regions in the same country.

We quantify the general equilibrium effects on economic growth of improving the quality of institutions at the regional level in the context of the implementation of the European Cohesion Policy for the European Union and the UK. The direct impact of changes in the quality of government is integrated in a general equilibrium model to analyse the system-wide economic effects resulting from additional endogenous mechanisms and feedback effects. The results reveal a significant direct effect as well as considerable system-wide benefits from improved government quality on economic growth. A small 5% increase in government quality across European Union regions increases the impact of Cohesion investment by up to 7% in the short run and 3% in the long run. The exact magnitude of the gains depends on various local factors, including the initial endowments of public capital, the level of government quality, and the degree of persistence over time.

We assess the macroeconomic impact of the EU cohesion policy investments deployed during the 2014-2020 programming period, employing updated data on planned expenditures, which in most Member States will take place until 2023. We use the spatial dynamic general equilibrium RHOMOLO in order to quantify the direct and indirect effects of the policy investments in the NUTS 2 regions of the EU within a 20-year time frame. The results suggest that the impact of the policy is sizeable, especially in the less developed regions of the EU. Accordingly, regional disparities are shown to decrease thanks to the policy intervention. The policy also has a positive impact at the EU level, GDP in the EU being 0.4% higher in 2021 compared to a scenario without cohesion policy.

This study uses both econometric and modelling techniques to quantify the macroeconomic impact of regulatory reforms removing barriers in the European Single Market for services that have taken place in the European Union between 2006 and 2017. It also provides scenario analyses of the impact of a number of hypothetical additional reforms aimed at further reducing regulatory restrictions. The results of the modelling simulations indicate that the regulatory reforms implemented between 2006 and 2017 will result in discounted cumulative gains of 2.1% of GDP by the year 2027. Furthermore, ambitious additional reforms from 2017 onwards would generate an additional growth potential of 2.5% of GDP by 2027. Combining the realised and potential gains would result in a cumulative gain in GDP of 4.65% and a rise in employment of more than 300,000 full time equivalents by 2027. More conservative hypotheses on the additional reforms from 2017 onwards would lead to a GDP cumulative gain of 3.22% by 2027.

We employ the spatial dynamic general equilibrium model RHOMOLO to estimate the economic impact of the 2021-2027 Cohesion Policy in Bulgarian NUTS-2 regions and analyse the implications for growth and development in Bulgaria. The main investment areas covered by the policy fall into the following five fields of intervention: aid to the private sector, research and development, transport infrastructure, other infrastructure, and human capital. They are characterised by a varying degree of positive demand and supply side effects on regional and aggregate development, which, together with the level of the shocks, determine the impact on GDP. We find that a projected €10.9 billion of Cohesion Policy funding would increase Bulgarian GDP by 3.4% above its baseline value at the end of the implementation period in 2030 and by 2.4% ten years later. Our results suggest that there is no systematic equity-efficiency trade-off in Bulgaria which mainly arises as the consequence of low spillovers in the capital city region versus the strictly higher spillovers observed in the rest of the country's regions. We conclude that a balanced Cohesion Policy portfolio would foster a high impact on national GDP, maintain a high intensity of spillovers and reduce regional disparities in Bulgaria.

Recent technological developments open up possibilities for introducing a vast number of novel mobility concepts in urban environments. One of these new concepts is urban air mobility (UAM). It makes use of passenger drones for on-demand transport in urban settings, promising high travel speeds for those willing and able to pay. This research aims to answer the question how benefits from UAM will be distributed, taking into account the spatial dimension and the differential impacts on low- and high-skilled households. We develop a framework that can more generally be used to assess the welfare impacts resulting from the introduction of novel transport modes. The development of an urban spatial computable general equilibrium model building on the polycentric modelling tradition developed by Anas and co-authors allows for an analysis of mutually dependent effects on the land, labour and product markets, triggered by changes on the transport market. Allowing for an endogenous spatial structure through the introduction of agglomeration effects and an amenity-based approach, the framework investigates the relevance of the initial spatial structure for the impact of the introduction of UAM. Incorporating different skill levels of households allows to assess location choice and travel behaviour for households with different characteristics. A numerical simulation of the model shows that the different initial spatial structures impose comparable welfare changes. Variations in UAM features like marginal cost, prices, land demand for infrastructure, vertical travel speed and access and egress times have a (much) more decisive impact on modal choice and welfare effects than the initial urban structure. Simulations show that considering households of different skill levels brings additional insights, as welfare effects of UAM introduction strongly differ between groups and sometimes even go in opposing directions.

We analyse the impact of the investments related to the European Cohesion policy in Portugal over the 2014-2020 programming period. We use the spatial dynamic general equilibrium model RHOMOLO to identify the direct and indirect effects stemming from a variety of spending categories and economic channels. The policy interventions are modelled with both demand and supply side shocks exerting short and long run effects, the latter being related to changes in labour productivity, transport costs, and total factor productivity. An important part of the analysis deal with the spillovers spreading the effects of the policy outside the borders of the regions in which the investments take place. Our results show that the €30 billion of Cohesion policy investments can increase Portugal's GDP by 3.5% at the end of the implementation period, and that additional benefits in terms of GDP and employment continue to materialise after the end of the monetary injections. Moreover, we present region-, Fund-, and field-of-intervention-specific results to give a complete picture of the impact of Cohesion policy in Portugal.

Using a spatial general equilibrium model, this paper investigates the resilience of EU regions under three alternative recessionary shocks, each of them activating different economic adjustments and mechanisms. Using a theoretical framework, we measure the vulnerability, resistance, and recoverability of regions and we identify key regional features affecting the ability of regions to withstand to and recover from unexpected external shocks. The analysis reveals that the response of regions varies according to the nature of the external disturbance and to the pre-shock regional characteristics. Finally, it seems that resilience also depends on factors' mobility.

The European cohesion policy is the EU's main investment policy and targets all regions and cities across the EU to support job creation, business competitiveness, economic growth, and sustainable development. In the 2014-2020 programming period, one third of the EU budget has been allocated to the projects under this policy. This report contains a macroeconomic impact assessment of the European cohesion policy with a focus on Polish regions. The analysis deals in particular with the spillover effects arising from the policy intervention resulting from indirect trade effects and other inter-regional interdependencies and interactions. The analysis shows that the policy has a positive long-run impact, lasting years after the end of the programmes. This reflects the fact that cohesion policy supports investments in key engines of growth improving the structure of the Polish economy.

This is the first study that attempts to assess the regional economic impacts of the European Institute of Innovation and Technology (EIT) investments in a spatially explicit macroeconomic model, which allows us to take into account all key direct, indirect and spatial spillover effects of EIT investments via inter-regional trade and investment linkages and a spatial diffusion of technology via an endogenously determined global knowledge frontier with endogenous growth engines driven by investments in knowledge and human capital. Our simulation results of highly detailed EIT expenditure data suggest that, besides sizable direct effects in those regions that receive the EIT investment support, there are also significant spatial spillover effects to other (non-supported) EU regions. Taking into account all key indirect and spatial spillover effects is a particular strength of the adopted spatial general equilibrium methodology; our results suggest that they are important indeed and need to be taken into account when assessing the impacts of EIT investment policies on regional economies.

The Regional Trade Flows and Input output Data for Europe are constructed at the regional NUTS2 level with sectoral NACE2 detail and developed for spatial macroeconomic modelling and social-economic analysis for answering a wide-range of policy questions, including policies related to investments in innovation, human capital, green infrastructure and Sustainable Development Goals. The Regional Trade Flows and Input output Data for Europe are particularly well suited for structural modelling such as spatial computable general equilibrium models, as all data are fully internally consistent. In the Regional Trade Flows and Input output Data all European regions are connected with each other via inter-regional trade flows, input use and output supply in form of regional trade matrices, input output tables and supply-use tables. This data base is result of a joint collaborative effort over a decade of several research institutes across Europe, including the Netherlands Environmental Assessment Agency (PBL), the European Commission (DG JRC) and the University of Groningen (Ivanova, Kancs and Stelder 2009, Thissen et al. 2014, Thissen et al. 2018, Ivanova, Kancs and Thissen 2019). Among others, the new EU Economic Modelling System (EU-EMS) developed within the EU Framework Programme for Research and Innovation makes use of the Regional Trade Flows and Input output Data for Europe.

This technical report illustrates a simulation performed to assess the likely economic impact of the Grand Paris Express investments on the Île-de-France and the other European Union regions, under the working assumption of a combined 1% increase in labour productivity due to better matching between skill supply and demand and a 1% increase in accessibility due to the project. Our simulations suggest an overall medium-term positive GDP impact for the EU as a whole (0.18%), for France (0.79%) and for Île-de-France (2.61%).

In this paper we assess the system-wide economic impact of the key financial instruments adopted by the European Union for the implementation of the regional policy: The Structural funds and The Cohesion Funds. We take a bottom-up approach by aggregating the 86 categories of expenditures defined in the Structural and Cohesion Funds into six main policy variables. The outcomes of the simulations are the results of a combination of demand-and-supply-side shocks that are implemented into the RHOMOLO spatial and dynamic general equilibrium model calibrated on a set of inter-regional Social Accounting Matrices for the year 2010. In our analysis we document the direct, indirect, and general equilibrium effects of the EU regional policy at the regional, national, and EU level. In the short-run, our simulation exercise suggests a pronounced variegate patters across EU regions. In the long-run, a more homogenous spatial distribution is detected. Moreover, we identify and quantify the interregional spillover effects arising from trade links and capital mobility.

Quantifying the economic effects of climate change is a crucial step for planning adaptation in developing countries. This study assesses the economy-wide and regional effects of climate change induced productivity and labor supply shocks in agriculture in Ethiopia. The study shows, in worst case scenario, the effects on national GDP may add up to -8% with uneven regional effects ranging from -10% in agrarian regions (e.g. Amhara) to +2.5% in urbanized regions (e.g. Addis Ababa). Cost-free exogenous structural change scenarios in labor markets and transaction costs may offset about 20-30% of the ripple effects of climate change. Therefore, the ongoing structural transformation in the country may underpin the resilience of the economy to climate change. Nevertheless, given the role of agriculture in the current economic structure of the country and the potency of biophysical impacts of climate change, adaptation in the sector is indispensable. Otherwise, climate change may hamper economic progress of the country, and make rural livelihood unpredictable.

Migration is one of the strategies used by populations to adapt to natural shocks and also to respond to economic policies. Climate change will probably have an impact on the productivity of factors and on the health of the population of the Latin America and Caribbean region, triggering migrations. In addition, policies aimed at reducing emissions (like carbon taxes) will change relative prices and the remuneration of factors and, in turn, will alter the allocation of labor between urban and rural areas. This paper explores the potential quantitative relevance of those population movements using a CGE version of the Harris-Todaro model. Two paradigmatic cases are considered: i) domestic or internal migrations, focusing on the case of Sao Paulo (Brazil) and ii) international migrations, analyzing the displacement of population from Bolivia and Paraguay to Argentina.

We develop an interregional computable general equilibrium model to help assess the ex ante impact of transportation infrastructure policies in Egypt. The model is integrated with a GIS network. We illustrate the analytical capabilities of the model by looking at the domestic integration of the country. Improvements of transportation costs among Egyptian governorates and of their links to the broader world economy are considered in stylized simulations. The results provide quantitative and qualitative insights (general equilibrium effects) into trade-offs commonly faced by policy makers when dealing with transportation infrastructure projects in a spatial context. In the case of Egypt, there seems to be an important trade-off between efficiency and regional equity: projects that produce potential higher impacts on national GDP also tend to contribute more to regional concentration., Resource replaces the TD NEREUS 01-2015" version published by Núcleo de Economia Regional e Urbana da USP (NEREUS).

The rapid growth of ASEAN economies, the People’s Republic of China and India (called ACI henceforth) — major drivers of Asia and the world economy—during the last five decades has caused significant strains on their scarce resources, particularly energy and contributed to serious problems of energy security, environmental degradation and climate change. In coming decades, these economies are expected to witness high growth, lack of adequate traditional energy sources, high dependence on imported energy, heavy reliance on energy-intensive industries, and rising transportation demands. In the coming decades, their energy demand may create serious challenges in terms of energy security. Adopting sustainable and innovative management practices and policies for key resources such as energy and mitigating environment and climate change problems are among major common challenges for all the ACI economies. This paper examines primarily on the ACI’s sustainable energy security outlook until 2030 through an overview of the ACI’s energy resources, production mix, consumption mix, emissions of greenhouse gases, and the state of the development of renewable, clean and new energy. The paper projects the ACI’s energy demand and its impact on carbon dioxide emissions until 2030 under different policy scenarios using a Computable General Equilibrium (CGE) analysis. Furthermore, the paper evaluates ACI’s sustainable energy security situation through examining ACI’s energy self-sufficiency, dependence on imported energy, energy import diversification transportation security and energy infrastructure financing. Lastly it provides some policy recommendation to achieve sustainable energy security in ACI.

This study develops a linked regional computable general equilibrium and micro-simulation (RCGE-MS) model to assess the regional economy-wide and poverty impacts of a US$36 million investment in tourism in the south of Haiti. The first social accounting matrix for Haiti with a base year of 2012/2013 was constructed to calibrate the model. This research addresses three key gaps identified in the tourism impact assessment literature. First, a destination-specific tourism demand and value chain analysis was used to calibrate the shocks implemented in the model. Second, the RCGE-MS approach moves beyond the representative household configuration to enable more robust analysis of tourism investment impacts on poverty and income inequality. Third, results of this modelling were used to inform a social cost-benefit analysis to provide greater transparency in the evaluation of trade-offs between investment alternatives. Results of this analysis showed a positive impact on sectoral activity, especially for the hotel and restaurant sector (182.1% in 2040) and a 2.0% increase in Gross Regional Product by 2040. The South's exports fell 4.7% below baseline and imports were 6.1% higher due to the inflow of foreign exchange, the appreciation of the regional real exchange rate, increased demand for most goods and services, and limited regional productive capacity. The rate of unemployment fell from 26% to 23%. The investment helped lift some of the region¿s poorest out of poverty, reducing the poverty headcount by 1.6 percentage points. Driving this result was an increase in employment, wages and non-labor income. The linked RCGE-MS approach proves to be a powerful tool for assessing how tourism investments affect regional economic activity and revealing the mechanisms through which tourism can contribute to increased employment opportunities and poverty reduction.

Regional economic impacts of fishing and hunting in Finland A state enterprise, Metsähallitus, administers state-owned land and water areas in Finland covering approximately 12 million hectares. One of the official administrative duties of Metsähallitus is to provide hunting and fishing opportunities for citizens. In 2013, more than 81,000 hunting licenses and 71,000 fishing licenses were granted. As indicated in the study, during one season, Metsähallitus hunting and fishing customers spent over EUR 33 million in the regions of licenses destinations. This paper indicates that hunters and fishers in Finland travel extensively and support the regional economy via their expenditures. In the summer and autumn of 2013, Metsähallitus carried out a survey that provided rich and up-to-date information that could be used for quantitative and qualitative research. For modelling purposes the private expenditures of hunters and fishers were grouped into trade, accommodation, restaurants, local public transport, and entertainment. However, the study also analysed these expenditures in more detail, presenting the personal expenditures per trip, per day of a trip, and per license. Moreover, the location of the expenditures was disaggregated into the region of license destination, the region of residence, and "on the way" between those two. For example, an average grouse hunter with a short-time (1?7 days) license in 2013 spent around EUR 150 per hunting trip within his or her region of residence, and more than EUR 440 per trip if the hunting area was located outside the region of residence. RegFin, a comparative-static regional Computable General Equilibrium (CGE) model was used in this study to calculate the wider economic impacts at a regional level, as well as to serve as an engine for an Excel-based assessment tool. The assessment of the regional economic impacts focused on basic economic indicators such as regional gross domestic product (GDP), household consumption, and employment. The results of the study indicate that hunting and fishing activities have a positive impact on regional economies. Just considering license destination regions in 2013, hunting and fishing on state-owned land increased regional GDP by EUR 6.4 million, created 86.2 person working years, and produced household consumption of EUR 36.6 million. Among the many conclusions, it was found that investments in regional services linked to hunting and fishing activities would increase the regional economic impacts of Metsähallitus customers.

We examine the effect of railway travel on urban spatial structure in a polycentric urban land use model. We focus on the role of access to the railway network. We find that if the number of train stations is limited, the degree of urbanization is higher around train stations, but the effect of railway travel on road congestion is small. By contrast, if train stations are omnipresent there is little effect on urban spatial structure, but a considerable decrease in congestion. With regard to the supply of train stations, these findings suggest that there is an important policy trade-off between congestion and urbanization.

This paper describes a methodology to develop a Computable General Equilibrium model with a sub-national detail starting from a global database and model presenting the country-level as the highest resolution. This procedure is demonstratively applied to Italy, but can be transferred to any country/macro-region, provided regional data availability. Increasing the spatial resolution of a CGE model can be particularly useful to capture local specificities not only in response to given policy shocks, but also to environmental impacts, as, for instance, those originated by climate change, which are highly differentiated spatially. Conceptual and practical issues are treated: we use an innovative method to estimate bilateral trade flows across sub-national areas and analyse the implications of different assumptions on both factor and good intra-country mobility. We carry out a simple experiment to test the robustness of our regionalized structure.

Spatial Computable General Equilibrium (SCGE) models are convenient methods of the analysis of the change of inter-regional economic interaction or regional benefit by policy shocks. Recent SCGE models have two main streams in terms of the assumption of market structure; perfect competition models and monopolistic competition models. Benefit measured by perfect competition based models is usually independent of economy of scale and therefore the policy assessment result is consistent with normal cost-benefit analysis. It is an important factor for practical welfare analysis when validity of policy implementation is discussed from a point of view of efficiency. On the other hand, monopolistic competition based models is suitable to theoretical framework of new economic geography field which highlights the economic agglomeration. Agglomeration effect is also an important factor from a point of view of regional economic development effects. Thus the both of two types of models have theoretical and practical merits respectively. However, the results of the model analyses of course depend on the model formulations and can be different in not only detail but also feature of benefit distribution. Understanding the difference of the model outputs by theoretical assumption is crucial theme of practical policy assessment. This paper attempts to compare the economic effects of a road transport development project estimated by a perfect competition based SCGE model and a monopolistic competition based SCGE model quantitatively. Our analysis emphasizes especially the differences in the magnitude of benefit and the regional distribution pattern of benefit because they are usually the largest interests of actual policy assessments. The results show that elasticity of substitution, which is a dominant parameter of monopolistic competition models as a key factor of markup, sensitively affects to benefit and its distribution. It mainly causes the difference of the outputs of the perfect competition based SCGE model and the monopolistic competition model, which implies that the elasticity parameter should be chosen carefully. We furthermore analyze the relationship between size of analysis target region and benefit as well as sensitivity analysis of model parameters. The analysis shows that the regional scale also influences to the benefit estimation in particular by monopolistic competition model. Finally, we summarize the tendency of model outputs of the two types of the models and points to keep in mind for the practical policy analysis by SCGE models. Key words: Spatial Computable General Equilibrium model, Perfect Competition, Monopolistic Competition JEL Classification: C68, R13, O18 Other Choice of Theme: H. Infrastructure, Transport and Communications

Application of a new spatial computable general equilibrium model for assessing strategic transport and land use development options in London and surrounding regions By Jie Zhu, Ying Jin and Marcial Echenique The Martin Centre, University of Cambridge, UK JEL Classification: C68, F12, F16, F17,O18, R13, R42 Key words: Computable general equilibrium; spatial modelling; increasing returns to scale; integrated land use and transport modelling This paper reports the application of our new spatial computable general equilibrium (SCGE) model for analyzing the wider effects of strategic transport and land use development options. We examine the insights afforded by a SCGE model relative to those provided by existing land use and transport models into the effectiveness of transport and land use strategies. We start from a static imperfect competition computable general equilibrium model for an open economy, and extend it to incorporate (1) Hicks-neutral agglomeration effects that arise from external increasing returns to scale induced from urbanization and transport improvements, (2) land as an explicit factor input to production, and (3) commuting and migration of labour in a dynamic labour market. These extensions are built on models of constant elasticity of substitution specified for production technology and utility functions, interregional trade pooling, concave-shaped iceberg transport costs, the Armington specification regarding product varieties, the Dixit and Stiglitz type of monopolistic competition among producers, and the concept of the spatial economic mass. Data from London and surrounding regions is used to calibrate and validate the model. We report its applications in studying suburban road capacity expansion, high speed rail links and suburban and exurban land supply. The model results obtained so far are in line with theoretical expectations and provide new quantification of the costs and benefits that feed into the assessment of those strategies. Some on-going and further developments of the model include (1) All exogenous parameters for setting up the model are subject to further refinement from conducting sensitivity tests with respect to the magnitude of the model responses, (2) Flows between zones can in the future be mapped on to transport networks, e.g. through linking to a detailed transport model, and (3) the model may be extended with a recursive dynamic structure for policy analysis by incremental policy horizons.

This study develops a policy model under the hierarchical administration system of the regional economy in Japan. In case of Japan, a hierarchy of national, prefectural, and municipal (city) administration exists, and a different regional policy in these each hierarchies can be set up. Generally, the policy and its evaluation might be different whether should give priority to national interests or to each region's interests. To show such a situation, quantitatively analysis by using the computable general equilibrium model (CGE model) is examined. Concretely, Kitakyushu City and Fukuoka City are taken up as an administrative region at the city level. Together with these two cities and surrounding areas, it becomes Fukuoka Prefecture. On the other hand, the case of including Yamaguchi Prefecture, the adjacent prefecture, in these regions exists. In this case, it can be called Northern Kyushu Area by combining Fukuoka Prefecture and Yamaguchi Prefecture, and such a large area also becomes important in the regional policy as higher hierarchy. Five regions including the rest of Japan are focused on this study. Moreover, due to availableness of the input-output tables of these regions, respectively, the data base to develop the CGE model is estimated after tabulating the interregional input-output table.