Regional Input Output Research Articles

Research on the impact of manufacturing servitization on environmental pollution: spatial econometric analysis of sulfur dioxide based on 284 prefecture-level cities

Using China’s regional input–output table, the paper constructs indicators of manufacturing servitization, matches manufacturing servitization at the regional level with city data, and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide (SO2) emissions within the classical Environmental Kuznets Curve (EKC) framework. The results show that manufacturing servitization can reduce SO2 emissions. Producer servitization and consumptive services can both significantly reduce industrial SO2 emissions. Transportation and warehousing servitization, information servitization, leasing, and commercial servitization, technology research and development servitization significantly reduce SO2emissions; technology research and development servitization, in particular, have the largest influence coefficient, while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant. The study also found that servitization reduced the SO2 emissions through technological innovation and industrial structure upgrading.

Multi-regional economic recovery simulation using an Adaptive Regional Input–Output (ARIO) framework

The economic repercussions of natural hazards extend beyond immediate damages, impacting more than the directly affected regions through trading ties and interrupted service provisions. The Adaptive Regional Input–Output (ARIO) model has been developed to assess these indirect impacts by considering changes in productive capacity and demand-driven output adjustments. We extend a recently refined ARIO model (R-ARIO) to conduct a multi-regional multi-sector analysis. This extension accounts for the geographical disparities in direct damages and inter-regional economic interactions. To illustrate the effectiveness of this approach, we present a case study of the 2011 Tohoku earthquake and assess its economic impacts across 13 prefectures in the East-Japan region. The paper further compares the outcomes of single- and multi-regional analyses to showcase the effect of inter-regional trading ties on economic resilience. Additionally, trade-offs involved in selecting the study area boundary for the multi-regional analysis are discussed.

Regional Industrial Effects in Germany from a Potential Gas Deficit

Abstract We estimate potential regional industrial effects in case of a threatening gas deficit. For Germany, the reduction leads to a potential decrease in industrial value added by 1.6 %. The heterogeneity across German states is remarkable, ranging from 2.2 % for Rhineland-Palatinate to 0.7 % for Hamburg. We emphasize the need for regional input-output tables to conduct economic analysis on a sub-national level, particularly when regional industrial structures are heterogeneous. The approximation with national figures can lead to results that differ both in magnitude and relative regional exposure. Our findings highlight that more accurate policy guidance can be achieved by improving the regional database.

The Impact of Gastronomic Tourism on the Regional Economy of Thailand: Examined by the Dynamic I-O Model after the Decline of COVID-19

It is reasonable to state that gastronomic tourism is an efficient tool that has the potential to refresh Thailand’s macroeconomic viability. With the aim of becoming a hub of tourism in Southeast Asia, Thailand’s tourism industry must urgently address and sustainably integrate gastronomic activities to navigate the troubled situation caused by its decline after the COVID-19 pandemic. This has led the authors to conduct a deep study on a regional input–output (I-O) table analysis for Thailand’s tourism system, specifically focusing on gastronomic activities and tourism industries. The tourism I-O data used in this study come from the official source provided by the Thailand Ministry of Tourism and Sport. Empirically, the results of the dynamic regional I-O model predict that Bangkok and its surrounding areas are the heart of gastronomic tourism development, driving income into Thailand’s economy. The eastern region stands as the second-largest area of gastronomy tourism, generating a positive impact on Thailand’s economy. On the other hand, the Northeast of Thailand receives less income from gastronomy tourism despite being the largest area in the country. Ultimately, there should be a greater emphasis on gastronomy tourism policies in order to fully maximize their potential for tourism development, stimulating every part of Thailand during the economic depression caused by COVID-19. Moreover, gastronomy tourism has the potential to play an important role in driving economic growth through the combination of cuisine and tourism development.

An agent-based model for the assessment of the ripple effect of disaster economic losses considering firms’ adaptive behaviors

Assessing the spatial and temporal ripple effect of disaster economic loss is essential for integrated disaster risk management considering disaster countermeasures dynamically and systematically. Traditional loss estimation models based on general equilibrium theory hardly take the ripple process into account, as they just focus on the equilibrium status of economic system. However, the debate is that system will not reach equilibrium at one stroke and firms' adaptive behaviors will also change the disaster ripple losses. This paper proposes an agent-based model to investigate this phenomenon: the economic linkages among micro-agents are established based on regional input–output table and firms' production behaviors are defined according to nested production functions. The 2020 flood disaster in Hubei Province, China, is taken as an application case which demonstrated the feasibility of agent-based model for assessing the economic loss ripple effect considering firms' adaptive behaviors. Several interesting findings from the application are also drawn. (1) The speed of loss ripple is influenced by the distance to the disaster-stricken region, while the intensity of loss ripple depends on the strength of interregional industry linkages. (2) Round by round ripple effects could be found in non-disaster regions due to the lagged impacts caused by damage of production capacities in other non-disaster regions. (3) Firms' adaptive behavior reduced the ripple losses nearly by 60 % and saved CNY 5.72 billion in this case study. Notably, the gains from overproduction behavior in non-disaster regions are critical, with reducing the loss of CNY 5.8 for every CNY 1 of overproduction.

Development of regional input-output tables for Northern Ghana: An analysis using location quotient methods

Development of regional input-output tables for Northern Ghana: An analysis using location quotient methods

Relationships and Interdependencies of the Agri-Food Sector in a Regional Economy: Employing an Input-Output Model

The agri-food sector has been stressed as an essential determinant for an economy, as its impacts contribute directly and indirectly to its growth in various ways; with its products, with its trade, both in outputs and inputs, and when the sector grows. The current work aims to capture the relationships and impacts of the agri-food sector in a regional economy through linkage analysis. Building upon the relationship marketing theory, this is achieved by utilizing an I/O model constructed through modifying the Generation of Regional Input-Output Tables (GRIT) regionalization technique and using the Flegg Location Quotient (FLQ). The relationships of the economic sectors resulting from the purchases and sales between them provide helpful information for the region’s economy. The results demonstrate that the agri-food-related sectors are closely linked in the regional economy, as the primary activities supply processing with raw inputs. Moreover, agri-food-related sectors have strong interconnections with the rest of the local economy and can induce economy-wide impacts. Accordingly, the interdependence between different economic sectors determines the agri-food sector’s economic impact.

Economic impact of resident and nonresident marine anglers to the local economy in Mecklenburg‐Western Pomerania, Germany

AbstractRecreational fisheries catches are increasingly considered in the assessment and management of mixed recreational‐commercial marine fisheries, while the contribution of recreational fisheries to the economy is often overlooked. Using a telephone diary survey targeting marine recreational anglers in Germany, we estimated the number of anglers and their expenditures over the course of 1 year (2014–2015). About 197,000 marine anglers spent €248 million in Germany. We then constructed regional input–output models and contrasted the economic impacts of resident and nonresident anglers fishing in coastal and transitional brackish waters of the state of Mecklenburg‐Western Pomerania in north‐eastern Germany. On a regional scale, the total economic impact was €210 million supporting 2044 jobs, nonresident anglers were responsible for eight times greater economic impact than resident anglers. Maintaining attractive fishing opportunities for the recreational fishing sector, specifically angling tourism, is critical for maintaining resource flows to local and regional economies.

The carbon footprint of regional tourism trips: insights from environmentally extended regional input output analysis

Tourism is an important and almost certainly increasing driver of anthropogenic climate change. However, intelligence on the total greenhouse gas emissions related to tourism trips – including travel to and from the destination – is limited, especially at sub-national destination scale. This paper uses an environmentally extended input-output approach to estimate the total greenhouse gas emissions consequent on inbound and domestic tourism trips in Wales, a region of the UK. We use the UN World Tourism Organisation (TSA) concept of visitors and trips to estimate the overall carbon footprint of tourism at around 3.4 megatons in 2019, 8.7% of total territorial emissions. We further compare these results with estimates for 2007 which suggests that there has been a modest reduction of under 2% per annum since 2007, but with significant data issues affecting comparability. Apparently slow progress in decarbonisation, including an increase in intercontinental visits to Wales over the period, suggest tourism here has not yet embarked upon a climate-responsible transformation.

Exploring Water Use in Mildly Water-Scarce Regions: A Structural Decomposition Analysis for Anhui Province in China

Because of severe water scarcity, it is crucial to quantify water use in China’s water-scarce regions and to analyze the factors driving its use. In this paper, we analyze the driving factors behind the water footprint from 2007 to 2017 in the mildly water-scarce region of Anhui Province, using regional input–output models and structural decomposition analysis. The results show the following: (1) Although the average virtual water intensity of Anhui Province decreased by 52.58% from 2007 to 2017, the water-use efficiency was still low; (2) During the study period, the total water footprint of Anhui Province increased by 25.06%, with an obvious upward trend; (3) From 2012 to 2017, the net export volume of virtual water in Anhui Province was positive, and the flow volume decreased by 78.87%; (4) Technological progress contributed the most to reducing the water footprint of Anhui Province, followed by the increased counter-urbanization rate as the second-largest driving force. The expansion of the scale effect, including the size of the economy and the size of the population, was the main negative driving force for the increase in Anhui’s water footprint. However, the proportion of economic scale in the water footprint drivers gradually decreased.

Industrial Embeddedness and Regional Economic Resistance in Europe

We study the role of local industrial embeddedness (the share of regional interindustry economic activity that is anchored to a region) on regional resistance (the difference between pre- and postcrisis employment) to the 2008 Great Recession (GR) in EU and UK NUTS-2 regions. The recession had profound effects in regional economies, which showed diverse performance based on their capacity to absorb the shock. The concept of economic resilience has been brought to the center of attention with several contributions exploring its determinants. However, the impact of the embeddedness of local economic systems in terms of sales and supplies has been largely unexplored. We use regional input–output tables to approximate the embeddedness of local economies, and we use fixed-effects and quantile regressions to test its relationship to regional resistance between 2008 and 2011. We find that during the GR, regional industries opted to change input rather than output markets. Additionally, embeddedness has a curvilinear relationship to regional resistance that varies across the distribution of regional resistance performance. Finally, at the industry level, we find regional embeddedness to be important to the resistance of manufacturing and financial and business services, and sectoral embeddedness to matter more for the resistance of construction and wholesale, retail, and information technology. Our findings highlight nuances that policy makers should be aware of in planning for resilience.

An alternative approach to estimating regional input–output tables: the KFLQ method

An alternative approach to estimating regional input–output tables: the KFLQ method

Construction of Regional Input-Output Table for Sarawak Economy

Construction of Regional Input-Output Table for Sarawak Economy

Development of a Regional Input-output Model for Environmental and Socio-economic Assessment of Renewable Energy

本研究では，地域における再生可能エネルギー技術の導入がもたらす環境・社会経済効果を評価するための再生可能エネルギー部門拡張産業連関モデル・地域版（Renewable Energy Focused Input-Output model for Region: REFIORegion）を開発している。REFIO-Regionの作成は次の２段階のプロセスで構成されている。第一に，国と47都道府県の産業連関表，経済センサス活動調査など各種統計を用いて，1,741 市区町村の産業連関表（地域内表）を作成している。 第二に，1,741市区町村を任意の２地域に分類して２地域間表とするとともに，12種の再生可能エネルギー技術に関わる部門を結合することで，２地域間産業連間モデル，すなわちREFIO-Regionを構築している。REFIO-Regionは，わが国の1,741市区町村の産業構造ならびに12種の再生可能エネルギー技術の技術構造を詳細に表現しており，各技術の地域レベルの導入効果を詳細に分析可能である。REFIO-Regionを用いて，18市町村で構成される熊本連携中枢都市圏に風力発電を導入した場合の地域経済効果についてケースタディを実施している。ケースタディの結果は風力発電と導入地域の特徴を反映したものとなっており，本モデルの有効性を示している。

Impact assessment of China's inter-provincial trade on trade-related sustainable development goals

Assessing progress towards achieving the Sustainable Development Goals (SDGs) is among the most pressing areas for sustainability research. Both international and inter–provincial trade has substantial impacts on sustainability. However, little is known about the impacts of inter–provincial trade on progress towards achieving the SDG targets and the relationships among SDG indicators through time and space. Here we, taking Chinese inter–provincial trade as a study case, used a spatiotemporal approach and the multi–regional input–output (MRIO) model to examine changes in six SDG indicators and their relationships within China in the year 2002, 2007, 2010, 2012, 2015, and 2017. The results showed that (1) Chinese inter–provincial trade improved the trade–related SDG target scores of 16 provinces out of the evaluated 30 provinces but reduced the trade–related SDG target scores of the remaining 14 provinces. (2) Chinese inter–provincial trade and distant trade were more beneficial for achieving the trade–related SDG targets in developed provinces (e.g., Beijing), which thus improved China's overall SDG target scores. In contrast, Chinese inter–provincial trade suppressed the trade–related SDG target scores of developing provinces (e.g., Guangxi). (3) Individual SDG indicators, SDG target bundles, and interactions among SDG indicators changed across both time and space. (4) The no–trade scenario in Hubei province during the COVID–19 pandemic will have a clearly inhibiting effect on China's overall SDG target scores. Besides, trade with adjacent provinces would improve Hubei's SDG target scores, while these trades have more negative effects (approximately 50–83% of provinces suffered from greater reductions in SDG target scores) on Hubei's adjacent provinces. Our study suggests the spatiotemporal dynamic characteristics of SDG indicators and their interactions deserve more attention, which can help identify the drivers behind these changing relationships.

A New Improvement Proposal to Estimate Regional Input–Output Structure Using the 2D-LQ Approach

The use of location quotients for the estimation of regional input–output tables has been found to be a useful and efficient tool to estimate intraregional production coefficients and multipliers. This paper considers some regionalisation methodologies based on location quotients for the estimation of input–output tables—some of which have hitherto not been analysed at the regional level—and studies which one provides the best estimation (best goodness of fit). We focus the analysis mainly on the accuracy of Flegg’s location quotient (FLQ) and two-dimensional location quotient (2D-LQ). The analysis makes use of the multiregional input–output table for Korea for the year 2015 to evaluate the accuracy of the 2D-LQ method against FLQ. A novel proposal for the determination of the parameters corresponding to the 2D-LQ method is presented. This proposal is evaluated in Korean regions and is also applied to Spanish regions. The results obtained from the research conclude the general superiority of the 2D-LQ method, thus corroborating the results of other studies at the national level as well as the validity of our proposal.

Some Specificities of Regionalization of Input-Output Models: Information Aspects

The article discusses the problems of constructing and using regional input-output tables, describes the features of disaggregating economic activities, and shows the most complex, missing in statistics, information arrays necessary for constructing regional input-output tables. A brief overview of the main methods of regionalization of intersectoral models used in domestic and foreign practice is made. The necessity of combining direct assessment methods necessary for the construction of tables and models of indicators and methods based on the use of indirect data is noted. The necessity of using production and distribution balances in natural indicators as the most important direction of improving national economic and regional input-output tables is shown, since the available natural indicators, as a rule, reflect the volume of production and consumption of products in full, and not only the part of it that is marketable. The special importance of increased requirements for information reflecting the current state of the economy of the country and regions is emphasized. The main applied results obtained with the help of intersectoral models as a tool for long-term forecasting of the national economy are presented. The features of modeling intersectoral relations of small regional economies and limitations of the use of regional input-output tables for assessing multiplicative effects arising in economies of this type (on the example of the Republic of Tyva) are considered.

Effects of COVID-19 on Adriatic and Continental Croatia tourism: a regional input-output perspective

The purpose of this article is to estimate regional economic impact of tourism in Croatia. Rich cultural heritage and natural resources are factors which have contributed to the rapid increase in tourist arrivals in Adriatic Croatia, especially after the removal of all barriers to free movement following Croatia’s admittance to the European Union. While tourism is one of the key sectors which has contributed to Adriatic Croatia’s growth and development, a high share of tourism in gross value added and employment has increased the region’s vulnerability to external shocks, such as the outbreak of COVID-19 pandemic in 2020. The estimation of tourism’s role in Croatia’s regions is based on the regional input–output model, which identifies total effects of tourist demand. Results of the study reveal structural differences in Croatia’s regional growth path. While Continental Croatia specialises in more sophisticated industrial sectors, the economy of the Adriatic region is strongly dependent on tourism. The decrease in tourist arrivals due to COVID-19 travel restrictions resulted in a significant decline in economic activity in Adriatic Croatia. Economic activity in the hospitality sector was most affected by decreased demand, but other sectors which deliver inputs required for tourism services were also significantly impacted.

Limited impact of COVID-19 recovery packages on near-term CO2 emissions pathways

Part of the economic recovery plans implemented by governments following COVID-19 is directed towards the energy transition. To understand the potential effects of these post-COVID green recovery packages on reductions of global greenhouse gas emissions until 2030, we investigated three different approaches. First, we analyzed simulation results of Integrated Assessment Models (IAMs) to infer the change in CO2 intensity of GDP that could result from post-COVID low-carbon investment plans. Second, we investigated the scenarios the International Energy Agency (IEA) provided based on a bottom-up energy system model. Combining the two approaches, we found that green recovery packages implemented and planned globally can lead to an emissions reduction of merely 1%–6% from the 2030 baseline levels at most. Third, we looked into the results of the Adaptative Regional Input-Output model, which simulates the dynamic effects of economic crisis and fiscal stimuli through supply chains following labor shortage. The third approach shows that the increase of activity driven by fiscal stimuli leads to a rebound of CO2 emissions even if they do not target carbon-intensive sectors. We conclude that green recovery packages targeting low-carbon technologies have a limited impact on near-term CO2 emissions and that demand-side incentives, as well as other policy efforts to disincentivize the use of fossil fuels, are also crucial for scaling up climate mitigation.

A Comparative Analysis on the Economic Effect of theRegional Industry by Standardization Method- Focusing on the Smart Tourism Industry -

본 연구는 제4차 산업혁명 및 코로나19로 큰 관심을 받고 있는 스마트관광산업의 정의, 분류 및 현황을 살펴보고, 2013년 및 2015년 지역산업연관표를 이용하여 스마트관광산업의 종합파급효과를 계산하고 그 변화를 비교해 보았으며, 스마트관광산업의 경쟁력 강화 방안을 제언하는 것을 목적으로 한다. 스마트관광산업의 현황을 사업체당 종사자 수로 살펴보면 관광산업이 활성화된 제주, 강원, 부산의 경우 2016- 2019년 중 연평균 증가율은 강원이 전국 평균보다 높고, 부산 및 제주는 역성장한 것으로 나타났다. 2019년 기준 사업체당 종사자 수는 세 지역 모두 전국 평균에 미치지 못하는 것으로 나타났다. 스마트관광산업의 2013년 및 2015년 국가 전체 생산유발계수, 부가가치유발계수, 취업계수(명/10억 원)를z-표준화, 십분위간-표준화, 선형-표준화 등 세 가지 표준화 방법에 따라 표준화를 수행한 이후, 각각의 개별 지표들에게 같은 가중치를 부여하여 종합지표인 ‘스마트관광산업 종합파급효과’를 계산하고 순위 차이를 비교해 보았다. z-표준화 방법이 다른 방법에 비해 상대적으로 우수한 것으로 나타났고, 경기, 대전, 충남, 대구, 경북, 울산등 6개 지역이 다른 지역에 비해 상대적으로 유리한 것으로 나타났다. 한편, 표준화 방법에 따른 Kendall의 순위상관계수(Kendall’s τ) 및 통계적 유의성을 계산한 결과 5% 유의수준에서 통계적으로 유의미한 것으로 판별되어 세 가지 표준화 방법 모두 유용성이 있는 것으로 판단된다. 따라서, 한 가지 방법으로 순위를 결정하기보다는 세 가지 방법을 모두 활용하여 종합적으로 판단하거나 다른 방법론을 활용하는 것이 바람직하다고 할 수 있다. 스마트관광산업의 경쟁력 강화를 위해 기존 관광산업 생태계에서 스마트관광산업 생태계로의 전환을 제안하였다.The purpose of this study is to examine the definition, classification, and current status of the smart tourism industry which is receiving great attention due to the 4th industrial revolution and COVID-19, calculate the aggregate economic effect of the smart tourism industry and compare its changes using 2013 and 2015 Regional Input-Output Tables, and suggest ways to strengthen the competitiveness of the smart tourism industry. Looking at the current status of the smart tourism industry in terms of the number of employees per business in Jeju, Gangwon, and Busan, where the tourism industry was activated, the average annual growth rate during 2016-2019 was higher than the national average in Gangwon, and negative growth in Busan and Jeju. As of 2019, the number of employees per business was found to be lower than the national average in all three regions. After standardizing the total national production inducement coefficient, value-added inducement coefficient, and employment coefficient in 2013 and 2015 of the smart tourism industry according to three standardization methods such as z-standardization, inter-decile range-standardization, and linear scaling-standardization, an aggregating indicator which measures the aggregate economic effect of the smart tourism industry was calculated by giving the same weights on all individual indicators and the ranking differences were compared. The z-standardization method was found to be relatively superior to other methods, and 6 regions including Gyeonggi, Daejeon, Chungnam, Daegu, Gyeongbuk, and Ulsan were found to be relatively advantageous compared to other regions. Meanwhile, as a result of calculating Kendall's rank correlation coefficient and statistical significance according to the standardization method, it was found to be statistically significant under the 5% significance level, indicating that all three standardization methods are useful. Therefore, it can be said that it is desirable to make a comprehensive judgment using all three methods rather than determining the ranking by one method or to use other methodologies. In order to strengthen the competitiveness of the smart tourism industry, we proposed a transition from the existing ecosystem of tourism industry to the ecosystem of smart tourism industry.