Input-output Framework Research Articles

Development of a distributive Three Gorges Project input-output model to investigate the disaggregated sectoral effects of Three Gorges Project

Research on the overall social, economic and environmental (SEE) impacts of water resources projects (WRP) has gradually attracted attention. However, the WRP-related indirect impacts as linked through various supply chains from a number of disaggregated sectors and their interactive relationship are rarely studied. Here in this study, under a general disaggregated input-output (IO) framework, a distributive Three Gorges Project input-output (DTGIO) model is developed to investigate the composite effects of Three Gorges Project (TGP) based on a disaggregated TGP-IO table for the Yangtze River economic belt (YREB). DTGIO model could facilitate exploring i) the interactions among key TGP-related effects from production and consumption sides; ii) the impacts of various TGP-induced changes on specific SEE sectors; iii) the detailed TGP water flow paths as induced by the final demand of each province in YREB. It is discovered that the TGP has the greatest impact on agriculture. Although the construction of the TGP submerged a large amount of land and adversely affected agriculture in the reservoir area, its effective flood control function can reduce flooding in the “land of fish and rice” and create favorable conditions for agricultural development. The connection between the TGP and the inner provinces of YREB is mainly realized by the hydropower generation sector. For the economic benefits of the TGP, the economic benefits of the investment of various sectors of the TGP are diversified, which should be adjusted according to the government's objectives. For the ecological effects of the TGP, the interaction of sectors (especially the irrigation service sector and hydropower generation sector on consumption side, and the hydropower generation sector and water supply sector on production side) should be valued and a sense of joint management for the relevant sectors of TGP should be established.

Environmental and Energy Implications of Meat Consumption Pathways in Sub-Saharan Africa

In sub-Saharan Africa (SSA), diets are largely based on cereal or root staple crops. Together with socio-cultural change, economic and demographic growth could boost the demand for meat, with significant environmental repercussions. We model meat consumption pathways to 2050 for SSA based on several scenarios calibrated on historical demand drivers. To assess the consequent environmental impact, we adopt an environmentally-extended input-output (EEIO) framework and apply it on the EXIOBASE 3.3 hybrid tables. We find that, depending on the interplay of resources efficiency and demand growth, by 2050 the growth in meat consumption in SSA could cause a growth in greenhouse gases emissions of 1.4 [0.9–1.9] Gt CO2e/yr (~175% of current regional agriculture-related emissions), which is an extension of cropping and grazing-related land of 15 [12.5–21] · 106 km2 (one quarter of today’s global agricultural land), the consumption of an additional 36 [29–47] Gm3/yr of blue water (nearly doubling the current regional agricultural consumption), an eutrophication potential growth of 7.6 [4.9–9.5] t PO4e/yr, and the consumption of additional 0.9 [0.5–1.4] EJ/yr of fossil fuels and 49 [32–73] TWh/yr of electricity. These results suggest that—in the absence of significant improvements in the regional sectoral resource efficiency—meat demand growth in SSA is bound to become a major global sustainability challenge. In addition, we show that a partial substitution of the protein intake from the expected growth in meat consumption with plant-based alternatives carries additional significant potential for mitigating environmental impacts. The policies affecting both farming practices and dietary choices will thus have a significant impact on the SSA and global environmental flows.

Input-output framework for actuated boundary layers

This work extends the input-output approach to the study of wall-bounded shear flows manipulated using actuators common in experimental flow control studies. In particular, we adapt this powerful analytical framework to investigate the flow response to specified geometric actuation patterns (e.g., different plasma actuators) that can be applied over a range of different temporal input signals. For example, the commonly studied steady-state (time-averaged) flow response corresponds to a superposition of step responses in our modeling framework. The approach takes advantage of the linearity of the transfer function representation to construct the actuated flow field as a weighted superposition of the flow responses to point sources of varying intensity comprising the actuation model. We first validate the proposed method through comparisons with numerical and experimental studies of the time-averaged behavior of a transitional boundary layer actuated using a dielectric-barrier discharge plasma actuator operating in constricted discharge mode. The method is shown to reproduce the streamwise velocity field and the vortical structures observed downstream from the tested plasma actuator configurations. We then demonstrate that the method provides even better agreement with the steady-state response of the boundary layer subject to actuation from arrays of symmetric plasma actuators arranged in both spanwise and serpentine geometries. These results indicate the utility of this extension to the widely used input-output framework in analyzing the effects of certain actuation modalities that have shown promise in flow manipulation strategies for drag reduction. An important benefit of this analytical method is the low computational cost associated with its use in extensive parametric studies that would be cost-prohibitive using experiments or high-fidelity simulations.

Robustness of Uncertain Switching Nonlinear Feedback Systems Against Large Time-Variation

For a multiple-input–multiple-output (MIMO) nonlinear feedback system, the robustness against uncertain time-variation (slow or infrequently large) in the feedback loop is investigated in an input–output framework. A couple of sufficient conditions in terms of bounds on average rates of time-variation for the system to be stable are derived. The conditions provide a useful tool for designing adaptive controllers for systems against uncertain large time-variation.

Analysis of the Structural Decomposition of the Textile-Clothing Industry in Bangladesh

Purpose: This paper aims to introduce the technology’s role and the final demand in the textile clothing industry’s growth path (TCI) of Bangladesh. Methodology: This study applies structural decomposition analysis in the input-output framework to measure Bangladesh’s textile–clothing industry structural changes. Structural decomposition analysis is also known as growth accounting in literature. Findings: This paper finds that, from 1975 to 1995, the TCI has grown due to huge domestic demand, from 1995 to 2015, this industry has grown due to export expansion. The technology was never a key factor over low–cost labor for the development of TCI in Bangladesh. Implications: For the sustainable development of the TCI in Bangladesh, domestic demand expansion is significant. Private and public policies should reflect this expansionary (domestic demand expansion) strategy. Originality: Previous studies on the TCI were mainly descriptive; there was no decomposition analysis in the input-output framework. Moreover, this paper decomposes the growth of the TCI into technical effect and final demand effect, which are new in the ready-made garment industry of Bangladesh.

Measuring technology and performance differentials among the Norwegian dairy farms

PurposeThe study measures the technology gap and performance of the Norwegian dairy farms accounting for farm heterogeneity.Design/methodology/approachThe analysis was based on a meta-frontier and unbalanced farm-level panel data for 1991–2014 from 417 Norwegian farms specialized in dairy production in five regions of Norway.FindingsThe result of the analysis provides empirical evidence of regional differences in technical efficiencies, technological gap ratios (TGRs) and input use. Consequently, the paper provides some insights into policies to increase the efficiency of dairy production in the country across all regions.Research limitations/implicationsThe author used a meta-frontier approach for modeling regional differences based on a single-output production function specification. This approach has commonly been used in the economics literature since Battese et al. (2004). To get more informative and useful results, it would be necessary to repeat the analysis within terms of multiple input-output frameworks using, for instance, the input distance function approach. Moreover, the author estimated the meta-frontier using the non-parametric approach, thus it is also a need for further analysis if the values are different by estimating using a parametric approach.Practical implicationsOne implication for farmers (and their advisers) is that dairy farms in all regions used available technology in the area sub-optimally. Thus, those lagging the best-performing farms need to look at the way the best-performing farmers are operating. Policymakers might reduce the gap is through training, including sharing information about relevant technologies from one area to another, provided that the technologies being shared fit the working environment of the lagging area. Moreover, some of the dairy technologies they use may not fit other regions, suggesting that agricultural policies that aim to encourage efficient dairy production, such as innovation of improved technology (like breeding, bull selection and improved feed varieties) through research and development, need to account the environmental differences between regions.Social implicationsFor both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize dairy farmers appear to bring some benefits in terms of more efficient milk production that, in turn, increases the supply of some foods so possibly making food prices more affordable.Originality/valueThe paper contributes to the literature in several ways. In contrast to Battese et al. (2004), the author accounts for farm-level performance differences by applying the model devised by Greene (2005), thus may serve as a model for future studies at more local levels or of other industries. Moreover, the author is fortunate to able to use a large level farm-level panel data from 1991 to 2014.

Potential Socioeconomic and Environmental Effects of an Expanding U.S. Bioeconomy: An Assessment of Near-Commercial Cellulosic Biofuel Pathways.

This paper showcases the suitability of an environmentally extended input-output framework to provide macroeconomic analyses of an expanding bioeconomy to allow for adequate evaluation of its benefits and trade-offs. It also exemplifies the framework's applicability to provide early design stage evaluations of emerging technologies expected to contribute to a future bioeconomy. Here, it is used to compare the current United States (U.S.) bioeconomy to a hypothetical future containing additional cellulosic ethanol produced from two near-commercial pathways. We find that the substitution of gasoline with cellulosic ethanol is expected to yield socioeconomic net benefits, including job growth and value added, and a net reduction in global warming potential and nonrenewable energy use. The substitution fares comparable to or worse than that for other environmental impact categories including human toxicity and eutrophication potentials. We recommend that further technology advancement and commercialization efforts focus on reducing these unintended consequences through improved system design and innovation. The framework is seen as complementary to process-based technoeconomic and life cycle assessments as it utilizes related data to describe specific supply chains while providing analyses of individual products and portfolios thereof at an industrial scale and in the context of the U.S. economy.

Drivers of energy-related PM2.5 emissions in the Jing-Jin-Ji region between 2002 and 2015

Sharp increases in energy consumption have led to increases in fine particulate matter emissions in the Jing-Jin-Ji region. In this study, PM2.5 emissions of various sectors were assessed from the production-, consumption-, and income-based perspectives by multiple principles accounting analysis. The key drivers of PM2.5 emission changes were identified by structural decomposition analysis, then the flow patterns were determined by input–output analysis. Consumption-based and income-based accounting methods were used to investigate PM2.5 emissions for 21 sectors using the production-based emission inventory in the Greenhouse Gas Air Pollution Interaction and Synergies model for the Jing-Jin-Ji region and an environmentally extended input–output framework. Structural decomposition analysis was then used to identify the socioeconomic drivers of changes in PM2.5 emissions in the Jing-Jin-Ji region between 2002 and 2015 from consumption- and income-based perspectives. Inter-provincial flow patterns for consumption-driven and supply-driven PM2.5 emissions were then identified by performing input–output analysis. The results indicated that transport and storage, electricity, hot water, gas, and water production and supply and services are the key sectors emitting PM2.5 from the production-, consumption-, and income-based perspectives, respectively. The emission intensity is a crucial socioeconomic driver affecting changes in PM2.5 emissions. The inter-provincial PM2.5 flow results indicated that Beijing is a consumption- and supply-driven net importer of PM2.5 emissions and Hebei is a net exporter. The results will help in the development of measures to mitigate demand-side and supply-side PM2.5 emissions and of coordinated multi-regional policies for the Jing-Jin-Ji region.

National systems of innovation in the Eurozone: Policy implications for Spain

This paper aims to understand which innovation inputs are more strongly related to innovation outputs in the Eurozone, and to derive policy implication for the Spanish convergence with Eurozone top players in terms of innovation. Drawing from the Global Innovation Index input-output framework we developed an alternative longitudinal index. The resulting country scores were used to construct a panel dataset composed of the 19 Eurozone members during the period 2013-2018, which were analysed through a series of multiple regression techniques. Results suggest a strong and positive influence of Business Sophistication on innovation outputs in Eurozone countries, derived mainly from the capacity of domestic firms to absorb knowledge. Possible implications for Spain could be derived from this fact, such as, for instance, encouraging inward foreign direct investment. Future research is needed to analyse the differentiated effects of such encouragement, as well as other surprising results of our study.

An extended Input–Output framework for evaluating industrial sectors and provincial-level water consumption in Indonesia

This paper provides an extended input–output (IO) model of sectoral water consumption for Bali, a province located in Indonesia that is a well-known global tourist destination. Currently, the province is experiencing water shortages, which leads to a burden and heavy competition in water usage among the various economic sectors. We developed a method for determining which industrial/economic sectors directly and indirectly consume the most substantial quantities of water and to what extent available water resources can become a restrictive factor in the development of leading economic sectors. We also used another method, backward and forward linkage indices, to identify the key sectors influencing water consumption. The results confirm that the agriculture sectors, including other food crops, non-food crops, and rice, consume the highest portion of total water consumption. However, indirect water consumption appears to comprise a vital share of total water resources. These sectors—including the livestock industry; food, beverage, tobacco, and coffee industries; the timber industry; wood products, crafts and minerals industry; trading; construction; and other processing industries—have the highest indirect consumption. Our model for direct and indirect water consumption is a useful tool for water and economic planning policymakers for devising water-saving policies and expanding the provincial economy.

National systems of innovation in the Eurozone: Policy implications for Spain

This paper aims to understand which innovation inputs are more strongly related to innovation outputs in the Eurozone, and to derive policy implication for the Spanish convergence with Eurozone top players in terms of innovation. Drawing from the Global Innovation Index input-output framework we developed an alternative longitudinal index. The resulting country scores were used to construct a panel dataset composed of the 19 Eurozone members during the period 2013-2018, which were analysed through a series of multiple regression techniques. Results suggest a strong and positive influence of Business Sophistication on innovation outputs in Eurozone countries, derived mainly from the capacity of domestic firms to absorb knowledge. Possible implications for Spain could be derived from this fact, such as, for instance, encouraging inward foreign direct investment. Future research is needed to analyse the differentiated effects of such encouragement, as well as other surprising results of our study.

Economic modeling of national energy, water and air pollution nexus in China under changing climate conditions

Both energy production and consumption could simultaneously bring about local water scarcity and regional air emissions. Identifying energy-water-air pollution interactions caused by final demand of energy is essential for gaining potential synergies and avoiding unintended economic losses when designing sustainable energy development pathways. Given that, an energy-water-air pollution nexus (EWAN) model is developed to examine the energy-related water and air pollution embodied in household consumption at different income levels. Under multi-regional input-output framework, an optimized three-dimensional coupling (OTC) model for coordinated multi-resources development is proposed to obtain potential system benefits. It is found that to meet electricity demand, air pollution problems in northern provinces have aggravated, and water consumption in southern provinces has increased. Reduced electricity demand in rich regions has a greater impact on the gross domestic product (GDP). Moreover, most economic changes occur in the demand changes of the electricity self-sufficient provinces. The impact of electricity demand by households at different income levels on air emissions and water usage is highly heterogeneous. For specific province, interfering with the consumption demand of Inner Mongolia is not conducive to both the economic and environmental system benefits. Although Heilongjiang is not short of water resources, its power generation mode needs to be adjusted.

Environmental and Energy Implications of Meat Consumption Pathways in Sub-Saharan Africa

In sub-Saharan Africa (SSA) diets are largely based on cereal or root staple crops. Together with socio-cultural change, economic and demographic growth could boost the demand for meat, with significant environmental repercussions. We model meat consumption pathways to 2050 for SSA based on several scenarios calibrated on historical demand drivers. To assess the consequent environmental impact, we adopt an environmentally-extended input-output (EEIO) framework and apply it on the EXIOBASE 3.3 hybrid tables. We find that, depending on the interplay of resources efficiency and demand growth, by 2050 global greenhouse gases emissions could grow by 1.4 [0.9-1.9] Gt CO2e/yr (~175% of current regional agriculture-related emissions), cropping and grazing-related land may cover additional 15 [12.5-21] · 106 km2 (one quarter of today’s global agricultural land), blue water consumption could rise by 36 [29-47] Gm3 /yr (nearly doubling the current regional agricultural consumption), the eutrophication potential could grow by 7.6 [4.9-9.5] t PO4e/yr and additional 0.9 [0.5-1.4] EJ/yr of fossil fuels and 49 [32-73] TWh/yr of electricity may be consumed. These results suggest that – in the absence of drastic resource efficiency or technological improvements – meat demand in SSA is bound to become a major sustainability challenge. We show that a partial substitution of the protein intake with plant-based alternatives carries significant potential for mitigating these impacts. The policies affecting farming practices and dietary choices will thus have a significant impact on regional and global environmental flows.

Structural decomposition analysis of Latvian agrifood sector as integral part of global market

Research background: the Latvian agrifood sector is continuously becoming more integrated in global markets. Imports and exports of agricultural commodities grow every year. At the same time, changes in output from agriculture and food processing are moderate. The main factors that can be used to characterize these sectors are employment, gross value added and income. The main causes of the changes of these three factors could be estimated by structural decomposition analysis. Purpose of the article: the objective of the research is the decomposition of the percentage changes over time in employment, gross value added and income in Latvian economy by their source: changes in intensities per unit of output, changes in the intermediate consumption and changes in the final demand structure. Methods: the traditional methods of the Input-Output framework, such as multipliers, elasticities, causative matrices enable the estimation of structural trends in economy sectors. However, they do not provide the share in the total impact of various factors on the changes in the economy. Structural decomposition analysis estimates the relative size of the impact of these factors within the total impact. Findings & Value added: the research results show rather large positive impact of final demand factor on employment, gross value added and income changes in both sectors. The impact of the intensities (reverse factor productivities), in turn, is large and negative. The impact of the intermediate demand is less marked. As the growth in final demand can be attributed solely to increase in export demand, this combined with the growth in labor productivity are the main drivers of employment changes in agriculture. The method can be effectively applied to other variables of interest for which the calculated intensities per unit of output make sense, such as carbon emissions, greenhouse gas emissions or energy input.

Evolving household consumption-driven industrial energy consumption under urbanization: A dynamic input-output analysis

Household consumption as one of the final demands is indirectly stimulating industrial production and industrial energy consumption (IEC). How household consumption drives IEC and how will household consumption-driven IEC evolve in the future especially under accelerating urbanization remains to be explored in depth. In this study, through identifying changes in the quantity and structure of household consumption in the input-output (I–O) framework, we examine the indirect IEC driven by urban and rural household consumption in China’s 8 groups of industries (27 sectors) in 2005, 2010, 2015 and 2017. Then integrating energy balance, material balance and value balance within the socioeconomic activities, we develop a dynamic simulation model to forecast household consumption-driven IEC from 2018 to 2030. It is found that total urban consumption-driven IEC increased substantially during 2005–2017 (599.8–1028.2 Mtce), also with an increasing proportion in total household consumption-driven IEC (74.5%–80.4%). Along with increasing residential disposal income, urban consumption-driven IEC is estimated to double in 2030. Heavy industry (Manufacture of Chemicals, Smelting and Pressing of Metals are prominent) maintains the leading contributor, followed by Services industry (Transport, Storage and Post is prominent). The gap between urban and rural consumption-driven IEC will continue widening accompanying urbanization. This study links urbanization with IEC via household consumption and introduces I–O simulation modeling into the prediction of consumption-based IEC. The findings of this study can provide insights into sounder management of IEC that combines household and industrial development in the context of urbanization.

Linking multisectoral economic models and consumption surveys for the European Union

Multisectoral models usually have a single representative household. However, more diversity of household types is needed to analyse the effects of multiple phenomena (i.e. ageing, gender inequality, distributional income impact, etc.). Household consumption surveys’ microdata is a rich data source for these types of analysis. However, feeding multisectoral models with this type of information is not simple and recent studies show how even slightly inaccurate procedures might result in significantly biased results. This paper presents the full procedure for feeding household consumption microdata into macroeconomic models and for the first time provides in a systematic way an estimation of the bridge matrices needed to link European Union Household Budget Surveys’ microdata with the most popular multi-regional input–output frameworks (e.g. Eurostat, WIOD, EORA, OECD).

Towards input–output‐based measurements of trade creation and trade diversion

AbstractThis paper discusses a new approach to quantify trade creation and trade diversion that relies on the structural decomposition analysis in an inter‐country input–output framework. The proposed measure captures the contribution of trade creation (diversion) between two countries to the GDP growth of the home country, partner country and third countries. For a trial calculation, the author uses the 2016 release of the OECD inter‐country input–output tables and focuses on the period 2000–11. Creation, diversion, but also contraction of trade flows are shown to be intrinsic to any pair of countries that may or may not be linked by a trade agreement. There is no evidence that the rise of free trade agreements in 2000s is associated with higher magnitude of these trade effects for an average country pair. The proposed approach is thought to be a useful alternative to econometric estimates of trade creation and trade diversion available to date.

The drivers of energy-related CO2 emission changes in Indonesia: structural decomposition analysis.

This study aims to decompose the changes in CO2 emission, in 1990-1995 and 2010-2015, to identify the main drivers of those changes at the sectoral level. Using energy input and input-output table, the emission changes were decomposed into six factors: energy intensity, carbonization factor, technology, structural demand, consumption pattern effect, and scale effect. This model would allow a given country to identify the impacts of energy consumption, energy mix, and production efficiency (as direct sources of emission) while paying close attention to their linkages with both the economic structure and the accretion of final demand. This research was the first attempt to decompose CO2 emission changes using the input-output framework in Indonesia. The results revealed that the scale effect was the main driving factor of emission in 1990-1995. In 2010-2015, embodied emission in the chemical industry, mining, rubber, and plastic industry significantly rose due to an increase in energy intensity. Meanwhile, the embodied emission in electricity, road and air transportations, and non-metallic mineral production rose due to inefficiency in production. The energy policy to improve efficiency and diversified primary energy seemed to be negative between 2010 and 2015. Consequently, the embodied emission from energy intensity factor in several energy-intensive sectors increased along with a lack of contribution to changes in primary energy composition. This study also demonstrated that there was a decline in structural demand for electricity and mining between 2010 and 2015, which contributed negatively to the emission and yet outdrew with the rise from scale effect.

Structured singular value of implicit systems

Implicit systems provide a general framework in which many important properties of dynamic systems can be studied. Implicit systems are especially relevant to behavioural systems theory, the analysis and synthesis of complex interconnected systems, systems identification and robust control. By incorporating algebraic constraints, implicit models provide additional versatility relative to the standard input–output framework. Problems of robust stability in implicit systems lead in a natural way to non‐standard structured singular value (μ) formulations. In this note, it is shown that for a class of uncertainty structures involving repeated scalar parameters, these problems reduce to a standard μ problem which is well studied and for the solution of which several numerical algorithms are available. Our results are based on a matrix dilation technique and the redefinition of the uncertainty structure of the transformed problem. The main results of the paper are illustrated with a numerical example.

Early estimates of the impact of the COVID-19 pandemic on GDP: a case study of Saudi Arabia

ABSTRACT The COVID-19 pandemic has affected economic sectors in a very heterogeneous way. In the early stages of the economic lockdown, only limited economic data, if any, related to the event were available. With the government’s discretionary measures to contain the infection, it became obvious that some sectors will suffer more than others. We have used this information within the input-output framework to calibrate demand shocks to individual sectors and to obtain early estimates of the impact on sectoral and overall GDP. Given the high level of uncertainty, we designed three scenarios, reflecting the severity of the shock, its sectoral distribution, and the time needed for recovery, and applied to the Saudi economy. The negative impact on headline GDP in 2020 is estimated to range from −4.8% to −9.8% compared to the baseline level, while the government’s fiscal countermeasures result in a positive effect of some 2.5% in real GDP. The study also shows how to accommodate a qualitative shift in economic conditions given the still-evolving pandemic. We consider the potential situation of a second wave of the infection that would enforce a protracted lockdown and imply second-round effects.