Spatial Computable General Equilibrium Model Research Articles

Multi-disciplinary seismic resilience modeling for developing mitigation policies and recovery planning

The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling. These data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as earthquakes. This paper presents a multi-disciplinary seismic resilience modeling methodology to assess the vulnerability of the built environment and economic systems. This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of communities. Two complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic perspective. The engineering model is developed using a probabilistic fragility-based modeling approach and is analyzed using Monte Carlo (MC) simulations subject to seismic multi-hazard, including simulated ground shaking and resulting liquefaction of the soil, to quantify the physical damage to buildings and electric power substations (EPS). The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their interdependency. The economic model consists of a spatial computable general equilibrium (SCGE) model that aggregates commercial buildings into sectors for retail, manufacturing, services, etc., and aggregates residential buildings into a wide range of household groups. The SCGE model employs building functionality estimates to quantify the economic losses. The outcomes of this integrated modeling consist of engineering and economic impact metrics, which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience goals. An illustrative case study of Salt Lake County (SLC), Utah, developed through an extensive collaborative partnership and engagement with SLC officials, is presented. The results demonstrate the effectiveness of the proposed methodology in quantifying the loss and functional recovery of infrastructure systems, the impacts on capital stock, employment, and household income and the effect of various mitigation strategies in reducing the losses and functional recovery time subject to earthquakes with varying intensities.

Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions

With growing regional economic integration, transportation systems have become critical to regional development and economic vitality but vulnerable to disasters. However, the regional economic ripple effect of a disaster is difficult to quantify accurately, especially considering the cumulated influence of traffic disruptions. This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect. A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system, and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster. The model is applied to the 50-year return period flood in 2020 in Hubei Province, China. The results show the following. First, when traffic disruption costs are considered, the total output loss of non-affected areas is 1.81 times than before, and non-negligible losses reach relatively remote zones of the country, such as the Northwest Comprehensive Economic Zone (36% of total ripple effects). Second, traffic disruptions have a significant hindering effect on regional trade activities, especially in the regional intermediate input—about three times more than before. The industries most sensitive to traffic disruptions were transportation, storage, and postal service (5 times), and processing and assembly manufacturing (4.4 times). Third, the longer the distance, the stronger traffic disruptions’ impact on interregional intermediate inputs. Thus, increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.

An application of land use, transport, and economy interaction model

Governments need to assess the benefits of transport projects to prioritize investments. It is imperative for governments to have tools that can closely estimate the actual benefits and impacts of investments in significant transport projects.Traditionally, the benefits of a transport project have been estimated by using a transport model, assuming fixed land use for the base and project case in the future. However, this approach cannot measure the impact of land-use changes as residents and businesses relocate to take advantage of lower travel and/or freight costs resulting from the project. Consequently, the benefits of the project may be under or overestimated, depending on its position within the transport network and how it reshapes land use patterns in the future. To overcome this drawback in existing models, this paper firstly presents a literature review of advances in the land use transport interaction model (LUTI), then discusses the development of a LUTI model for Victoria, Australia (VLUTI) by integrating the Victorian Integrated Transport Model with a Spatial Computable General Equilibrium model (SCGE). The land use component (SCGE) was developed to represent a highly resolved zone system, detailed classifications of occupations and industries, and spatial interactions via commuting, and trade in goods and services, and thus enables VLUTI to simulate a detailed and nuanced picture of land use and transport interactions in a complete economic environment.The literature review also indicates limited research in applying a LUTI to estimate land use change benefits. This paper presents an application of VLUTI by looking at differences in the conventional transport benefits under both static and dynamic land use scenarios. In the static method, the land use in the project case is unchanged from the base case. In the dynamic case, the land use in the project case, at a future point in time, is endogenously adjusted within VLUTI. It presents a method to correct, in the dynamic case, the benefits as estimated by the rule of a half, which usually assumes static land use. The paper concludes with suggestions for further developments and improvements of VLUTI such as incorporating an activity-based transport model and an environmental model to progress toward an integrated land-use, transport, economy, and environment model capable of assessing the full impact of a transport project in a holistic way.

Modeling economic impacts of mobility restriction policy during the COVID‐19 pandemic

The economic impacts of pandemics can be enormous. However, lockdown and human mobility restrictions are effective policies for containing the spread of the disease. This study proposes a framework for assessing the economic impact of varying degrees of movement restrictions and examines the effectiveness of this framework in a case study examining COVID-19 control measures in Japan. First, mobile network operators data and total employment statistics on a 500-meter grid scale are used to determine the status of mobility restrictions and impacts on consumption in 30 industrial sectors. Next, the economic impacts are assessed using a spatial computable general equilibrium (CGE) model, proven to yield valuable insights into the total economic impacts of natural disasters. In sectors that implement telework and e-commerce-wholesale/retail, finance/insurance, and communication sectors-estimates of production and GDP are obtained that are close to the actual figures. The current case study is limited to Japan, but similar analysis can be conducted by using the CGE model for each country and open mobility data. Thus, the framework has potential to serve as an effective tool for assessing trade-offs between infection risks and economic impacts to inform policy-making by combining with findings from epidemiology.

Transport Infrastructure and Regional Development: A Survey of Literature on Wider Economic and Spatial Impacts

The main purpose of the paper is to provide an overview of methods used to research the relationship between transport infrastructure investments and regional development, with a focus on wider impacts both in the traditional economic context (wider economic impacts or WEIs) and—which is a methodological novelty proposed by this paper—in the spatial context (wider spatial impacts or WSIs). In terms of methodology, research may be conducted using the following methods: cost benefit analysis (CBA) and multi-criteria analysis (MCA), accessibility and potential models, econometric production function estimates, regional modelling, trade and input-output (IO) modelling, Land Use-Transport Interaction (LUTI) or spatial computable general equilibrium (SCGE) models. In the European Union, approaches based on cost-benefit analysis (CBA), or possibly multi-criteria analysis (MCA), continue to prevail. Notwithstanding the availability of a wide range of methods for quantifying socio-economic impacts, the European Union recommends that wider economic impacts at the regional and national levels be assessed by means of qualitative approaches. This being the case, it is recommendable for the European Commission to take broad-ranging action towards ensuring that the effects of transport infrastructure investments are assessed by means of a broader range of approaches.

The economic damage of COVID-19 on regional economies: an application of a spatial computable general equilibrium model to South Korea.

We developed a spatial computable general equilibrium model of South Korea to assess the spatial spillover effects of the COVID-19 pandemic on South Korea’s regional economic growth patterns. The model measures a wide range of economic losses, including human health costs at the city and county level, through an analysis of regional producers’ profit maximization on the supply side and regional households’ utility maximization on the demand side. The model’s findings showed that if the level of spatial interaction decreases by 10% as a result of social distancing policies, the national gross domestic product drops by 0.815–0.864%. This loss in economic growth can be further decomposed into 0.729% loss in agglomeration effect, 0.080–0.130% loss in health effect associated with medical treatment and premature mortality, and 0.005% loss in labor effect. The results of the models and simulations shed light on not only the epidemiological effects of social distancing interventions, but also their resultant economic consequences. This ex-ante evaluation of social distancing measures’ effects can serve as a guide for future policy decisions made at both the national and regional level, providing policymakers with the tools for tailored solutions that address both regional economic circumstances and the spatial distribution of COVID-19 cases.

Risk caused by the propagation of earthquake losses through the economy

The economy of a country is exposed to disruptions caused by natural and man-made disasters. Here we present a set of probabilistic risk indicators, the Average Annual Loss (AAL) and the Loss Exceedance Curve (LEC), regarding to production, employment, Gross Domestic Product (GDP), Gross Regional Product (GRP), export volume, inflation, tariff revenue, among others, due to earthquakes. All indicators are computed using a systematic probabilistic approach, which integrates the seismic risk assessment with spatial computable general equilibrium models, both robust and well-known frameworks used worldwide in their respective fields. Our approach considers the induced damage and frequency of occurrence of a vast collection of events that collectively describe the entire seismic hazard of a country, giving us a better and more complete understanding of the full consequence of earthquakes. We illustrate this approach with an example developed for Chile.

Regional economic effects of the Ring Road project in the Greater Tokyo Area: A spatial CGE approach

AbstractWe build a spatial computable general equilibrium model to assess the spatial economic impacts of the completion of ring road sections on the highway network system in the Greater Tokyo Area. Although every prefecture obtains positive benefits in terms of the prefectural sum, some municipalities experience negative benefits. The outputs of the service sector are less tradable than those of the primary and manufacturing sectors, and they increase for a broader area. The regions with net production increases in all sectors gain positive benefits. Meanwhile, several municipalities whose production decreases in all sectors experience welfare improvements.

Impact of autonomous vehicles on the choice of residential locality

ABSTRACT Introducing autonomous vehicles (AVs) reduces generalized transportation costs and encourages people to relocate. Understanding the subsequent changes in urban structure can help predict the future development of urban economies and policies. Transportation connects multiple zones in cities, and by improving traffic flow and ease directly impacts the economies of various markets. Each direct impact then also indirectly affects related markets. Therefore, a spatial computable general equilibrium model that connects multiple zones via a transportation network is suitable for analyzing the impact of a new transport system. This study constructs a model to simulate the effects of AVs on residential location choice. The results show that increased prevalence of AVs steers people toward suburbs with poor public transportation. Thus, high-income workers react more to technological progress, while low-income workers react more to lowered ownership costs. Consumers’ location choices and budgets also affect residential zones’ development. Therefore, regional policy goals must be clarified and appropriate target consumer groups set when introducing AVs.

Going electric: Environmental and welfare impacts of urban ground and air transport

• We study welfare and environmental effects of electric modes in cities. • Electric cars reduce CO 2 emissions despite increasing travel and congestion. • The resulting welfare losses may dominate the gains from reducing CO2. • Welfare effects of UAM depend on initial mode choice and the way of introduction. • Substituting gasoline (electric) cars, UAM decreases (increases) emissions. This research aims to assess the broader impact of electric mobility in urban settlements, paying attention to both electrified ground and air transport. Considering electric cars as well as electric passenger drones, often referred to as UAM (urban air mobility), we use an urban spatial computable general equilibrium model to assess the welfare and environmental impacts of a transition to electric mobility. A numerical simulation of the model shows that a transition from gasoline to electric cars yields major emission reductions, while leading to welfare losses due to tax-induced market distortions. Introducing UAM into a gasoline-car city leads to marginal overall welfare gains. Introducing UAM into a city with electric cars results in welfare losses. While introducing UAM as an alternative to gasoline cars decreases CO 2 emissions, the introduction of UAM as alternative to electric cars leads to increasing emissions.

Will urban air mobility fly? The efficiency and distributional impacts of UAM in different urban spatial structures

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.

Will urban air mobility fly? The efficiency and distributional impacts of UAM in different urban spatial structures

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.

Simulation framework of China's Territorial Spatial Planning Model (CTSPM) based on Spatial Computable General Equilibrium Model (SCGE) and its application in land and space safety simulation

Simulation framework of China's Territorial Spatial Planning Model (CTSPM) based on Spatial Computable General Equilibrium Model (SCGE) and its application in land and space safety simulation

Synergy effects of highway investments on the Turkish economy: An application of an integrated transport network with a multiregional CGE model

We develop a Multi-Regional Spatial Computable General Equilibrium (TurkSCGE) model for economic analysis of highway projects, estimating their impacts on regional welfare and economic outcomes in Turkey. The framework integrates a transport sub-model that estimates minimum distances with a multiregional Computable General Equilibrium model that estimates economic aggregates. TurkSCGE identifies eight sectors in each of 11 regions. Three experiments explore the impacts of decreases in transportation margins from ‘distance shortening’. The three highway projects involved are estimated to yield a combined increase in GDP of 1.6%. However, the new highways in eastern Turkey, connecting eastern regions to each other and the west are shown to be best options for improving welfare in poorer regions.

A dynamic spatial CGE approach to assess economic effects of a large earthquake in China

This study evaluates the economic impact of a major earthquake on regional economies in China. Our dynamic spatial computable general equilibrium model divides China into 30 regions/cities based on a multi-regional input–output table. It encompasses a decentralized economy of utility-maximizing households and profit-maximizing firms. Drawing from historical data, we simulate an unpredicted and a predicted earthquake striking China's Bohai Economic Rim and calculate the dynamic and spatial impacts before and after each. We analyze two considerations: pre-quake investments to mitigate the effects of earthquakes and post-quake expenditures to recover from them. Results show that mitigating investments accelerate economic recovery in the Bohai Rim and across all of China. This finding indicates their importance and that of spatial resilience policy in the event of an earthquake.

Regional economic effects of transport infrastructure development featuring trade gateway region-asymmetric spatial CGE model approach

Port, or airport, is an essential infrastructure for international trade. Actually it is impossible to export/import for island countries without such port infrastructure. International freight transport system includes not only the infrastructure facilities but also the specialized procedure of international cargo handling and trading in the “trade gateway” region. It means that the situation of transport, or trade, system is asymmetric between the trade gateway region and other regions.This paper proposes a methodology based on spatial computable general equilibrium (SCGE) model framework taking into account of the asymmetric aspects of trade gateway region explicitly. The model describes the role of export and import sector in the trade gateway region, which do not exist other hinterland regions. We then apply the model to Japanese economy divided into two regions, trade gateway (Tokyo) and rest of Japan. Some transport development scenarios are evaluated quantitatively. A sensitivity analysis remarks the discussions regarding the effects of elasticity assumptions.

SPATIAL PRICE EQUILIBRIUM AND THE TRANSPORT SECTOR: A TRADE‐CONSISTENT SCGE MODEL

In spatial computable general equilibrium models, interregional trade ought to play an important role in determining the spatial price equilibrium. Although the Armington assumption is commonly employed to describe cross‐hauling, many of the existing models do not explicitly consider the behavior of transport firms. This paper presents a framework that is compatible with the Armington assumption and explicitly considers transport activities. In the model, the trade coefficient takes the form of a potential function, and the equilibrium market price becomes similar to the price index in the context of new economic geography. The features of the model are investigated by using the minimal setting, which comprises two nontransport sectors and three regions. Because transport costs are given exogenously, the commodity prices are determined relative to them. The model can be described as a system of homogeneous equations, where an output in one region can arbitrarily be determined similarly as a price in the Walrasian equilibrium.

Policy measures to promote mid-summer drainage in paddy fields for a reduction in methane gas emissions: the application of a dynamic, spatial computable general equilibrium model

Rice production is affected by climate change, while climate change is simultaneously accelerated by methane gas (CH4) emissions from paddy fields. The rice sector must take suitable mitigation measures, such as prolonging mid-summer drainage (MSD) before the rice flowering period. To propose a mitigation policy, this study aims to demonstrate the environmental and economic effects of MSD in Japanese paddy fields by using a dynamic, spatial computable general equilibrium (CGE) model and crop model; the study also considers environmental subsidies with a carbon tax scheme to promote MSD measures. The results demonstrate that climate change under the 8.5 representative concentration pathway (RCP) scenario will reduce rice prices and rice farmers’ nominal income due to bumper harvests until the 2050s. Promoting MSD in paddy fields can prevent a decrease in farmers’ nominal income and effectively reduce CH4 emissions if all farmers adopt this measure. However, some farmers can potentially increase their own yield by avoiding MSD under high rice prices, which would be maintained through other farmers’ participation. A strong motivation exists for some farmers to gain a “free ride,” and an environmental subsidy with a carbon tax can help motivate farmers to adopt MSD. Therefore, the policy mix of prolonging MSD and environmental subsidies can increase all farmers’ incomes by preventing “free rides” and decrease greenhouse gas emissions with a slight decrease in Japan’s GDP.

A socioeconomic analysis of ride-hailing emergence and expansion in São Paulo, Brazil

This paper estimates the socioeconomic impacts of the emergence and expansion of e-hailing services in São Paulo, Brazil. Combining data from a major service provider, individual level data from a representative travel diary survey and a structural traffic network simulation, we evaluate the impact of e-hailing on commuters' travel time and accessibility. We then estimate the effect of these changes on workers' productivity. Finally, using a Spatial Computable General Equilibrium (SCGE) model, we estimate the effect of these productivity shocks on broader economic outcomes. Our main results indicate that 83% of current e-hailing trips derived from trips that were previously made by traditional motorized private modes. We also find that the current e-hailing supply has mostly negligible effects on travel times and congestion; however, some individuals experienced important accessibility gains due to the emergence of this alternative mode. We then simulate e-hailing expansion and development scenarios, including the case of larger vehicle occupancy. Total economic activity expands by 1.089% if average vehicle occupancy reaches 3 passengers per trip and all motorized private trips are substituted by e-hailing.

Mobility in cities: Distributional impact analysis of transportation improvements in São Paulo Metropolitan Region

This paper evaluates the impacts of transportation investments/policies using a spatial computable general equilibrium (SCGE) model integrated to a travel demand model. In order to enhance our understanding of the distributional impacts of transportation improvements in Brazilian cities, we simulate the impact of different types of mobility investments in the Sao Paulo Metropolitan Region (SPMR). To explore further the income effects of infrastructure investments, we also conduct microsimulation exercises integrated to the SCGE results. We look at 10 different scenarios, ranging from a series of infrastructure-related interventions – considering the expansion of the mass-transit public transportation network – to policies that focus on monetary disincentives to the use of cars. The simulations results suggest trade-offs between efficiency and equity.