Input-output Tables Research Articles

A study of key techniques in mathematical input-output modeling in the field of management accounting

Abstract In this paper, we explore the integration of a stochastic input-output model based on uniform distribution into management accounting systems to enhance operational efficiency in enterprises. The model is formulated as the mathematical expression of an input-output table, focusing on the structure of the direct consumption coefficient matrix. By applying this model to the financial data of Y Iron and Steel Enterprise in W City, we evaluate the enterprise’s competitiveness and input-output performance. From 2019 to 2023, the company’s capital rate increased markedly from 0.0235 to 0.0868, reflecting a stronger resilience against lousy debt risks. Furthermore, we observed substantial growth in assets, deposits, and loans, with 2023 figures at 0.4965, 0.5839, and 0.3899, respectively. These metrics highlight the rapid development of the financial market and expansion opportunities. Our analysis demonstrates the utility of input-output models in management accounting to qualitatively assess and optimize product output and sales, thus ensuring greater overall operational efficiency.

Network analysis of economic sectors in the world economy

We consider a network of intermediate inputs trade between sectors of OECD Countries’ in 2020. Centrality indices are used to identify most vulnerable sectors in the network of intermediate inputs trade between 45 manufacturing and non-manufacturing sectors of 76 countries. The network is based on the official data of inter-country input-output tables published in 2023 by OECD. We apply new centrality indices to identify sectors, which might be under the risk in case of an economic shock.

G–7 and BRICS countries in global value chains

G–7 and BRICS countries play important roles in the world economy and global politics. The aim of the article is to answer the research question: “How participation of G–7 and BRICS countries in global value chains has been changing since 1995?”. To answer this question global value chains participation indexes were calculated. They were derived from Inter-Country Input-Output Tables. The value-added of this study stems from employing Input-Output Tables delivered by two institutions (Organization for Economic Co-operation and Development and Asian Development Bank). Consequently, article presents indexes calculated on the basis of two datasets. Combining two databases enabled to conduct study for quite long period (1995–2022). Analyzing the changes of global value chains participation indexes of G–7 and BRICS countries, we can distinguish following phases of internationalization: period of rapid globalization (1995–2008), global crisis and economic rebound (2009–2011), period of slowbalization somewhat strengthened by coronacrisis (2012–2020), and another recovery (2021–2022). This finding lead us to the conclusion that fast internationalization came to a halt in 2008 and since global financial crisis globalization has been quite slow despite some periods of recovery. Thus, there is an implication for more detailed research on slowbalization – its grounds, tendencies and prospects (whether fast internationalization is possible in the future; what is the role of economic policy in stimulating the pace of globalization).

Enigma of Nickel Export Ban: Understanding Its Impact through Input-Output Analysis

The nickel ore export ban policy has drawn pros and cons in various circles. This study aims to analyze the impact of the nickel ore export ban on other sectors of the economy and the interrelationship between one sector and another. This study uses secondary data in the form of Indonesia's Input Output Table Total Transactions at Basic Prices in 2016 derived from BPS publications and data on the number of Ferro-nickel exports in 2020 derived from UNData publications, which are then analyzed using the input-output method and presented using descriptive quantitative analysis. Based on the research results, electricity and gas procurement are the economic sectors with the most significant backward linkage. In contrast, the manufacturing sector achieves the most significant forward linkage value. In addition, the electricity and gas procurement sector also has the most significant output multiplier value, followed by the construction and manufacturing sectors. The increase in Ferro-Nickel exports due to the nickel ore export ban has considerably impacted the economy regarding both domestic and import output, especially in the manufacturing industry sector. Thus, nickel ore processing activities depend on capital goods and other imported raw materials. The study's implication shows that the export of Ferro-Nickel as part of the mining and quarrying sector impacts the output of other sectors to increase overall economic growth.

Characteristics and Influencing Factors of Provincial Industrial Convergence Networks in China

Abstract The 20th National Congress of the Communist Party of China proposed accelerating the promotion of Chinese-style modernization, placing higher requirements on regional economic development. In this context, interregional industrial convergence has become a new driving force for achieving high-quality economic development and regional industrial transformation and upgrading. Using the 2017 interregional input-output table provided by Carbon Emission Accounts and Datasets (CEADs), this study constructs a directed weighted network from both the supply side and the demand side, with “province-industry” as the node and the real flow between industries as the edge weight. Network analysis is used to investigate the overall status of industrial convergence in China, as well as differences according to industry and region. Finally, an exponential random graph model (ERGM) is used to examine the influencing factors and effects of network formation. The results show the following: (1) the industrial convergence relationship between regions in China is transitive and reciprocal, and the overall tendency of the network is one in which output capacity is greater than absorption capacity. (2) The marginal flow of manufacturing and services occupies an absolute advantage in China’s industrial convergence network, in which mid-end manufacturing and producer services are the most prominent. (3) Industrial convergence between provinces has formed a hierarchical spatial layout of “output-conduction-absorption”. In the absorption layer, the breadth and depth of Beijing’s industrial integration are characterized by absorption-dominant development. In the output layer, Shanghai’s capital-intensive industries have a strong external radiation capacity and generally show open-led development. (4) Interregional industrial convergence tends to occur in areas with similar economic levels and output value levels, showing a coordinated development trend of high-level output and low-level absorption, which is also affected by location proximity relationships, regional technology gaps, and employment population gaps. This research shows that China’s inter-provincial industrial convergence network generally shows the characteristics of spatial hierarchy, significant industry differences and multi-factor drivers.

Modifying national industrial structure for reducing heavy metals in China: A nexus-based multi-objective optimization approach

Heavy metals (HMs) exhibit significant toxicity and can lead to a range of health issues. Certain HMs share common emission sources, necessitating an exploration of the nexus among various HMs for achieving collaborative reductions. Considering the efficacy and feasibility of industrial modification to environmental pressures, this paper proposes a novel nexus-based optimization approach based on nexus analysis, multi-region input-output (MRIO) table, and multi-objective optimization to mitigate atmospheric HMs. The atmospheric HM emission inventory in 2017 is first compiled. Subsequently, the Integrated Nexus Strength of HMs Risk (HMR-INS) is proposed and employed to determine the range of sectoral output variations. Finally, a multi-objective optimization approach is employed based on the MRIO table in 2017. Compared with the traditional optimization method, the proposed approach performs better regarding HM-related risks and total output, leading to a 1.9 million tons increase in reduction on HM-related risks and a 1.37 trillion yuan increment in total output. Some further analyses are also given to provide feasible solutions for industrial modification, which considers both the economic efficiency and the stability of the industrial structure.

Navigating the Intricate Relationship between Investments and Global Output: A Leontief Matrix Case Study of Romania

This research delves into the intricate dynamics underlying the impact of investments on global output, employing the Leontief matrix as a robust analytical framework. Investments wield a profound influence on economies worldwide, with varying effects contingent upon investment types, development levels of countries, and external factors such as trade conflicts and global shocks. The diverse range of investment forms, including physical capital, human capital, R&D, and technological investments, engenders distinct implications for productivity, innovation, and efficiency. Developing and developed economies navigate unique trajectories, with investments playing a pivotal role in bridging infrastructure gaps, improving technology, and spurring growth. However, external disruptions, such as trade wars and global shocks, introduce an element of complexity, reshaping investment patterns and altering global output trajectories. This study centers on harnessing the Leontief matrix’s prowess to evaluate the interplay of investments and global output, focusing on the Romanian economy. By analyzing input–output tables, encompassing 105 branches aggregated into 10 sectors, the research captures the intricate connections between economic segments. Notably, the Romanian context reveals the volatility of the matrix coefficients, an outcome of ongoing transitional processes, technological advancements, and fluctuating relative prices. In unraveling the intricate threads weaving investments and global output, this study contributes to a nuanced comprehension of these multifaceted interactions. The findings underscore the significance of tailoring investment strategies to specific economic contexts and advocate for robust frameworks, such as the input–output model, to inform policy decisions and drive sustainable growth in an increasingly complex global economy.

How does manufacturing servitization effect global value chain upgrading? Tests based on the dual perspectives of “participation” and “division position”

Manufacturing servitization has become an important trend in the development of global manufacturing. Under the policy goal of global value chain upgrading, it is of great significance to discuss how manufacturing servitization affects the participation and position in global value chains (GVCs). Based on the OECD Input-Output Tables (OECD-ICIO) from 2008 to 2018, we calculate the level of manufacturing servitization in major economies. At the same time, based on the TIVA database, two indicators reflecting the upgrading of the global value chain are calculated from the dimensions of “participation” and “division position”. This paper empirically examines the mechanism and effect of manufacturing servitization on the upgrading of GVCs. Our findings reveal the following: (1) Manufacturing servitization has a significant enhancement effect on global value chain upgrading. (2) Manufacturing servitization can affect the upgrading of GVC through “cost reduction effect, technology spillover effect and specialization effect”. (3) Manufacturing servitization in developing countries has a greater promoting effect on the upgrading of GVC(4) For manufacturing industries with different levels of technological development, the promotion effect of manufacturing servitization on high-tech industries is more obvious. This paper has two main implications: On one hand, the government should not only increase support for the service sectors, but also promote the innovative development of the service sectors. On the other hand, it is necessary to improve the level of opening up to the outside world, make full use of the positive “spillover effect” of high-quality service elements, and promote the integration of production-oriented services and manufacturing.

The role of indirect oil and natural gas revenues in the Russian government budget

ABSTRACT The Russian federal and consolidated government budgets accrue large revenues directly from oil and natural gas, mostly from royalties and export fees. We use Russian Input-Output tables and other economic statistics to estimate how much revenue flowed to these budgets indirectly due to government spending of direct revenues in 2016–21. Although the addition of indirect revenues to the federal budget is modest (8–10 Russian rubles per 100 rubles spent), the corresponding increase in consolidated budget is quite sizable (26–30 rubles per 100 rubles spent). Given the high degree of political and economic centralization in Russia, the impact on the consolidated budget is more important than the impact on the federal budget. In addition, we speculate about the changing role of oil and natural gas budget revenues in the current environment and the near future.

Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis

The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations.

Analyzing market power of the agricultural industry in Asia

The study of market power in the primary foods industry is of high interest to policymakers seeking to help develop low-income countries, due to its potential source to create market inefficiencies and hamper economic development. Recent studies have provided ample empirical evidence, that market power has been increasing nearly continuously since the 1980s. Nevertheless, due to the (un)availability of firm-level data, most research is constrained to analyzing firms within industries of a few high-income with a particular focus on manufacturing and service sectors. This paper proposes to remedy this gap in the literature by using aggregate data contained within the Eora Input-Output Tables and a procedure based on Generalized Maximum Entropy to provide estimates of the markup for the primary foods industry (defined as the agriculture, hunting, logging and fishing industries) for 43 countries in Asia. We document a large heterogeneity based on a country's income level classification. Furthermore, measures of globalization are seen to significantly reduce markups. Opening up to trade might therefore be an attractive option to policymakers seeking to stimulate economic efficiency.

The energy-saving effect of industrial chain synergistic division: Evidence from China's industrial chain

Under the influence of global trade policies, countries gradually build their entire industrial chains, and industrial policies show a localized development trend. In this context, what impact will the industrial chain localization policy have on the low-carbon transition and high energy efficiency? It is significant for achieving the energy conservation and emission reduction goal. Therefore, this paper uses non-competitive input-output tables from 2002 to 2017 to construct China's domestic industrial chain panel data. We combined the econometric model to explore the influence of industrial chain synergistic division on energy intensity. The research found that the industrial chain synergistic division effect can significantly reduce energy intensity. The results were robust after some endogeneity tests. Secondly, the energy-saving effect brought by the synergistic division is more obvious in high-energy dependence and high-stage industrial chains. There is still room to improve the production efficiency brought by the division network effect. Finally, the industrial chain synergistic division can reduce energy intensity by improving labor productivity, enterprise productivity, and enterprise competition mechanism. This study can provide targeted policy recommendations for China to achieve structural energy-saving. It can also provide a reference for other countries to achieve carbon neutrality.

Gauging Effects of Hypothetical Extraction Method on Transport Linkages in India

Transport infrastructure is imperative for sectoral growth and economic progress. To gauge the impact of reduced contributions by the Railway and Other Transport sectors on other sectors in India, we use the Hypothetical Extraction (HE) based methodology to analyse the impact of such changes on outcomes of different sectors. Five Input-Output Transaction Tables (IOTT), between the years 1993-2014, are aggregated into 22 sectors. Methodologically, sector pair-wise correlations and sectoral groupings are identified in the transport sector. Induced elimination of Railway and Other Transport sector contributions are used to capture sectoral dependencies. Changing patterns in ‘Key’ sector compositions are further identified. Manufacturing, Mining and Quarrying, Construction, Storage and Warehousing and Electricity appear significantly correlated with Transport. Extraction causes sizeable output loss (around 60 perent) for the Manufacturing sector. ‘Self-extraction’ results in declining loss of output for transport sectors, whereas, Electricity and Storage and Warehousing remain ‘Key sectors’ in the post-extraction economy. An important implication emerging from our analysis is that dynamic relational dependencies across other sectors must be considered for future investments in transport infrastructure.

An input trade model with Keynesian unemployment: Bridging a gap between trade theory and international Input–Output analysis

AbstractThis study presents a trade model with (1) intermediate inputs, (2) link commodities, and (3) Keynesian unemployment. The model has linear input coefficients, stable commodity prices, and short‐run adjustment of the quantity supplied on the occasion of demand changes, making it compatible with international input–output tables and analysis. Given production techniques, labor endowments, upper limits of unemployment rates, markup rates, and final demand in each country, this model specifies feasible trade patterns and determines commodity prices, wage rates, gross outputs, employment/unemployment rates, national income, income distribution, and trade volumes/values for each pattern. Starting with a two‐country, three‐commodity case, this model expands to a multi‐country, multi‐commodity case.

Simulation study on the effect of differentiated carbon tax adjustment on CO2 emissions reduction in China from the perspective of carbon footprint

The carbon tax is an efficient environmental and economic method for lowering CO2 emissions, and effective carbon taxes should not only aim to reduce CO2 emissions but also consider their impact on socio-economic and resource utilization. The carbon footprint reflects actual carbon emissions and trade connections between sectors, providing a reference for levying carbon taxes on different sectors and examining their impact on the economy. This study utilizes the 2017 non-competitive input-output table of China and CO2 emissions and water consumption data from 27 sectors. Firstly, the research calculates carbon and water footprints of each sector through input-output analysis. Then, utilizing the input-output price model, the article compares the effect of differentiated carbon taxes on CO2 emissions and GDP across sectors in China, examining both direct carbon emissions and carbon footprint. Lastly, the survey constructs a carbon tax optimization model, aiming to maximize carbon and water footprint reduction while minimizing reduction in labor compensation. The key findings are: (1) Different sectors display varying characteristics in terms of direct carbon emissions and carbon footprints. 19 sectors exhibit higher direct carbon emissions than carbon footprints, while 8 sectors show the opposite. (2) Implementing carbon taxes on all sectors in China based on direct carbon emissions and carbon footprints effectively reduces CO2 emissions. However, at the same tax revenue, a reduction of 10^4 yuan in GDP leads to a further decrease of 0.47 × 10^6 tons of CO2 emissions from the carbon footprint perspective compared to direct carbon emissions. (3) In the optimal differentiated carbon tax plan based on carbon footprints, water production sector bears the highest carbon tax at 5.45 yuan/ton, while electricity production sector bears the lowest at 0.1 yuan/ton. This plan declines CO2 emissions by 7.82% and water consumption by 6.21%, but also results in a 0.02% decrease in GDP. The research findings recommend that sectoral differentiated carbon taxes consider economic development and resource impacts. Implementing refund policies to compensate for the economic losses caused by carbon taxes is essential, while also conserving resources and reducing CO2 emissions. These recommendations provide valuable guidance for the future introduction and implementation of differentiated carbon tax policies.

Tracking household carbon inequality in China: Composition effect or coefficient effect?

Reasonable allocation of carbon emission reduction tasks requires addressing household carbon inequality. This study aims to track characteristics of household carbon inequality in China using the recentered influence function (RIF) based on the Household Tracking Survey data in 2018 and the multi-regional input–output table. The Oaxaca–Binder decomposition based on RIF further decomposes household carbon inequality based on spatial heterogeneity into composition and coefficient effects. The results indicate that (1) household carbon inequality is widespread in China, generally close to the 60/30 distribution, favouring high-income families. Furthermore, (2) increases in income, wealth and economic burden and declining marriage rate promote household carbon inequality, which is suppressed by the development of education and the Internet and the increase in car ownership. Additionally, (3) the carbon inequality of urban households is smaller than that of rural households, which is contributed by the composition effects of family size, education, car ownership, Internet development and the coefficient effect of income and housing. Finally, (4) under the composition effect of family size and the coefficient effect of income, the household carbon inequality in the eastern region is smaller than in the central and western regions.

The economic fitness of nations in value added. 2000–2014

In this paper, we explore the Economic Fitness (EF) indicator from the World Bank Database that measures the nations level of international competitiveness. At the same time, using input–output tables, we present our estimations of this new metric, replacing the revealed comparative advantages (RCA) from exports in gross value with an estimate of RCA from exports in domestic value-added (DVA). We find that between 1995 and 2015, there is a positive relationship between Economic Fitness and per capita GDP for low and middle-income countries. Besides, we also show that the estimations of the EF using the domestic value-added content of exports changed significantly from 2000 to 2014 since there has been a widening gap between global exports in gross value and exports in value-added. The latter suggests that, given the increasing levels of productive links at the international level, the competitiveness of nations is also conditioned by how they participate in global production networks.

Unequal prefecture-level water footprints in China: The urban-rural divide

Water is vital for inclusive human well-being and economic growth, but water and its benefits are not equally distributed to all. The water gap between city dwellers and rural folks was not well understood. In this paper we assessed prefecture-level urban and rural water footprints (WFs) in China, using an improved multi-region input-output (MRIO) table with resolved urban and rural final consumption data. The assessment provided a quantitative foundation for evaluating and explaining urban and rural water use inequality from the consumption perspective. The results showed that per capita urban WF was on average 2.1 times per capita rural WF. The urban-rural WF divide constituted an important contribution to spatial WF inequality, in addition to provincial-level and prefecture-level differences. Compared to previous provincial-level WF analyses, this high-resolution prefecture-level urban and rural analysis showed clear evidence of economically developed urban areas as hotspots of large WFs. Specifically, our results provided a quantitative assessment revealing that 10 % China's population (urban residents in 51 prefectures) appropriated 25.8 % of the national WF. The dominant driving factor for urban-rural per capita WF disparity in all the prefectures was the consumption level, accounting for on average about 84 % of the disparity. There is an urgent need to leverage socio-economic development and urbanization against equitable and sustainable water use. The results have implications to equitable and sustainable water management from a broader macro-economic view.

RELATIONSHIP OF THE MINING SECTOR TO THE ELECTRICITY AND GAS PROCUREMENT SECTOR IN WEST PAPUA PROVINCE USING INPUT OUTPUT ANALYSIS

Linkage analysis is a method used to understand the economic structure of a region. This analysis can also be used to figure out how much influence a sector has on other sectors based on the input and output tables for each sector. This research was conducted to analyze the forward and backward linkages of the mining and quarrying sector to the electricity and gas procurement sector in West Papua Province, both directly and indirectly. The data used in this research is sourced from the West Papua Province Input Output Table Domestic Transactions Based on Producer Prices 2016 Updated 2021. The method used in this research is a descriptive quantitative method. From the results of this research, it was found that the value of backward linkages in the mining and quarrying sector was more significant than the value of forward linkages, both directly and indirectly, to the electricity and gas procurement sector. Thus, the mining and quarrying sector requires more output from the electricity and gas procurement sector as input, compared to the electricity and gas procurement sector's need for the output of the mining and quarrying sector.

The Significance of Participation in the Global Production Network to Economic Development: An Econometric Analysis of BRICS+T Countries

With globalization, the international fragmentation of production (IFP) splits the production process of final goods and services into several stages undertaken in different countries integrated into global production networks. BRICS + T countries have rapidly participated in the (IFP) process especially after 2000s. The main purpose of this paper is to analyze the nexus between BRICS+T countries’ participation in the global production networks and their economic development. The vertical specialization rate, as an indicator of this participation, had been calculated utilizing OECD Input-Output Tables. Subsequently, the development index was calculated utilizing economic-technological and cultural-institutional indicators published by World Bank. The vertical specialization’s impact on development was estimated utilizing the CS-ARDL estimator. The results revealed that while the vertical specialization has a statistically significant positive impact on development in the short term, a positive but not statistically significant impact was recorded in the long term. Konya (2006) causality test was performed to examine the causal relationship among the selected variables. The results revealed a one-way causality running from development to vertical specialization in China and Turkey and a one-way causality running from vertical specialization to development in Brazil. No causality relationship could be detected in other countries included in the analysis.