Input-output Matrix Research Articles

O IMPACTO ECONOMICO DOS DESEMBOLSOS DA BELOTUR COM O CARNAVAL DE BELO HORIZONTE EM 2018: UMA APLICAÇÃO DA MATRIZ INSUMO-PRODUTO

This study deals with the estimation of the economic impacts provided by the BeloHorizonte Municipal Tourism Company (Belotur) disbursements in 2018. It also aimsto understand how the event intervened in order to understand the contributionsunder the lens of expanding revenue, generating employment and income from thedisbursements made by Belotur. The method used was the Input-Output Matrix. Forthe matrix construction, it was necessary to analyze the published extracts related toBelotur expenses with the carnival and to carry out a classification of thedisbursements of Belotur according to the National Classification of EconomicActivities - CNAE. After these procedures, it was possible to estimate the impacts ofcarnival, which resulted from Belotur's disbursements, have shown very positiveresults in the economy, significantly increasing the values of Minas Gerais’production, value added, work earnings of the local population and also provided thecreation of jobs.

Inoperabilidade do setor de extração de minério de ferro: consequências sobre a economia brasileira

Recentemente, no estado de Minas Gerais tem ocorrido desastres com o setor de minério de ferro, tal como o que ocorreu na cidade de Mariana em novembro de 2015 e também no município de Brumadinho em janeiro de 2019, ambos causados por rompimentos de barragens. Essas tragédias além de ter um impacto social como a de morte de pessoas, também traz consequências para os demais setores da economia brasileira. Utilizando a abordagem de inoperalização de matriz de insumo-produto, o artigo tem como objetivo averiguar como a interrupção de atividade no setor de extração de minério de ferro no estado de Minas Gerais se dissipa para os demais setores. Os resultados obtidos sugerem que além do próprio setor de extração de minério de ferro, os setores mais atingidos por essa inoperalização, embora em menores proporções, são os setores de produção capital físico, como máquinas, equipamentos e automóveis, além de combustíveis.

Structural decomposition of variations of carbon dioxide emissions for the United States, the European Union and BRIC

Abstract The historical responsibility of the countries that have promoted the accumulation of carbon dioxide since the industrial revolution, mainly the United States, Russia and the European Union, and the responsibility of the increase in current emissions of emerging countries like Brazil, India and China, determine the moral duty to reduce and adapt their economies to solve the problem of climate change. Therefore, it is important to measure the variations in carbon dioxide emissions from these countries and the effort made to reduce them. The objective of the study was to decompose the variations of carbon dioxide emissions into technological and final demand effects using the input-output matrix of the United States, the European Union (EU, 27 countries), Brazil, Russia, India and China (BRIC). The results showed that the US and EU decreased their emissions respectively by 12.4% and 5.9%. The US achieved emission reductions mainly due to the intensity effect (sector’s own emissions) while the EU by technology effect (production chain’s emissions). It was caused by the adoption of new technologies and modifications of the energy matrix. Brazil, Russia, India and China (BRIC) respectively increased their emissions by 13.3%; 2.9%; 68.5% and 121.5%. The BRIC showed efforts to adopt new technologies to reduce emissions. However, changes in the structure and volume of final demand caused positive and superior effects to the technological effects of increasing emissions, especially in India and China.

O debate desenvolvimentista no Brasil e o papel da indústria: novos resultados de antigas lições

Resumo O artigo contribui para o debate desenvolvimentista no Brasil, a partir de dados obtidos na matriz de insumo-produto brasileira de 2014. Uma vez estimada a matriz com dados do IBGE, o artigo calcula os impactos de aumentos de investimento em termos de efeitos de encadeamento, geração de empregos, salários, produção e requisitos de importações, dos 20 setores nos quais o IBGE divide a economia brasileira, tirando conclusões sobre o papel da indústria na alavancagem do desenvolvimento econômico.

Dynamic Output-Feedback Control for Chemical Stirred Tank Reactor System with Multiple Time-Delays: A Lyapunov–Krasovskii Functional Approach

This paper addresses the dynamic output feedback control problem for a class of nonlinear multiple time-delays system. First, the system is decomposed into two subsystems based on the input matrix and output matrix. Second, a dynamic compensator is employed for the first subsystem, and then the output feedback controller is designed based on the second subsystem and compensator. With a new Lyapunov–Krasovskii functional, we show that the closed-loop time-delays system is stable and the designed controller make the solutions of the system convergent to an adjustable bounded region. Compared with the previous works, the proposed dynamic output feedback technique is more flexible and the required conditions on the considered systems are less conservative. Finally, the simulations for a discrete-time chemical stirred tank reactor case are performed to verify the effectiveness of the method.

Coordinated Energy Management for Micro Energy Systems Considering Carbon Emissions Using Multi-Objective Optimization

To promote the utilization of distributed resources, this paper proposes a concept of a micro energy system (MES) and its core structure with energy production, conversion, and storage devices. In addition, the effect of demand–response on the operation of a MES is studied. Firstly, based on uncertainties of a MES, a probability distribution model is introduced. Secondly, with the objectives of maximizing operating revenue, and minimizing operational risk and carbon emissions, a multi-objective coordinated dispatching optimization model was constructed. To solve this model, this paper linearizes objective functions and constraints via fuzzy satisfaction theory, then establishes the input–output matrix of the model and calculates the optimal weight coefficients of different objective functions via the rough set method. Next, a comprehensive dispatching optimization model was built. Finally, data from a MES in Longgang commercial park, Shenzhen City, were introduced for a case study, and the results show that: (1) A MES can integrate different types of energy, such as wind, photovoltaics, and gas. A multi-energy cycle is achieved via energy conversion and storage devices, and different energy demands are satisfied. Demand–response from users in a MES achieves the optimization of source–load interaction. (2) The proposed model gives consideration to the multi-objectives of operating revenue, operational risk, and carbon emissions, and its optimal strategy is obtained by using the proposed solution algorithm. (3) Sensitivity analysis results showed that risks can be avoided, to varying degrees, via reasonable setting of confidence. Price-based demand–response and maximum total emission allowances can be used as indirect factors to influence the energy supply structure of a MES. In summary, the proposed model and solution algorithm are effective tools for different decision makers to conceive of dispatching strategies for different interests.

Procedural Justice in Algorithmic Fairness

As algorithms increasingly take managerial and governance roles, it is ever more important to build them to be perceived as fair and adopted by people. With this goal, we propose a procedural justice framework in algorithmic decision-making drawing from procedural justice theory, which lays out elements that promote a sense of fairness among users. As a case study, we built an interface that leveraged two key elements of the framework---transparency and outcome control---and evaluated it in the context of goods division. Our interface explained the algorithm's allocative fairness properties (standards clarity) and outcomes through an input-output matrix (outcome explanation), then allowed people to interactively adjust the algorithmic allocations as a group (outcome control). The findings from our within-subjects laboratory study suggest that standards clarity alone did not increase perceived fairness; outcome explanation had mixed effects, increasing or decreasing perceived fairness and reducing algorithmic accountability; and outcome control universally improved perceived fairness by allowing people to realize the inherent limitations of decisions and redistribute the goods to better fit their contexts, and by bringing human elements into final decision-making.

REGIONAL INPUT-OUTPUT MATRICES AND AN APPLICATION TO ANALYZE A MANUFACTURING EXPORT SHOCK IN MEXICO

Based on the national Input-Output Matrix (IOM) 2012 calculated by INEGI, we estimate with the Flegg approach four regional Input-Output Matrices (RIOMs) using Banco de México’s regionalization (Northern, North-Central, Central and Southern). These RIOMs are employed to evaluate the impact on regional gross output, value added and employment from a 10,000 million dollar shock on Mexican manufacturing exports. The results show that the effects on the absolute values of gross output, value added and employment in the North are clearly larger than those estimated for the other regions. Another finding is that the total effects of the regional shocks tend to concentrate in the manufacturing sector, with the highest concentration observed in the North, and the lowest in the South. It is also shown that the North is, by far, the region experiencing the greatest change in its value added relative to GDP, followed by the North Central, the Central and the South. The results suggest a strong linkage between the manufacturing sector and tertiary activities, particularly commerce and services in the central regions, as well as between manufacturing and oil and gas extraction in the South.

Propagation of financial shocks in an input-output economy with trade and financial linkages of firms

Firms are connected through the production network, in which the production linkages coincide with financial linkages owing to delays in input payments that amount to a form of trade credit. In this paper, I investigate the roles of these interconnected production and financial linkages in the propagation of financial shocks. Empirically, I find, based on U.S. input-output matrix and loan data, that the upstream propagation of financial shocks is stronger than the downstream propagation. Theoretically, I elaborate a model that can capture this pattern of shocks, of which trade credit is an important component. Moreover, the model reflects the fact that trade credit attenuates the propagation of financial shocks when shocks are relatively small through the sharing of liquidity and amplifies their propagation when shocks are relatively large through illiquidity contagion.

Economic evaluation of the effects of exerting green tax on the dispersion of bioenvironmental pollutants based on multi-regional general equilibrium model (GTAP-E)

ABSTRACT The present study calculates the temporal value of energy money based on green scenario of tax on the dispersion of bioenvironmental pollutants using global trade analysis project-energy substitution (GTAP-E) and investigates the changes brought about in carbon dioxide, GDP along with CIF for 2016 in Iran and eventually presents an evaluation of such sectors as coal, oil, gas, and petroleum products. The results indicated that the implementation of green tax scenario along with technological progress causes reduction by −0.19% in temporal value of pollution money in coal sector and the effect of monetary value of energy carriers on oil was also found reduced by −0.67% and the percentage reduction is about −0.1 in contrast to the other countries. At first, the direct and indirect coefficients (Leontief inverse) and the multiplying coefficients of bioenvironmental pollutants were computed using input-output matrix table technique. It was figured out that the highest pollution is caused by CO2 in this sector. But, the highest pollution in agriculture and mine sectors, substantially as a result of gasoil consumption, is caused by CO that is currently showing an ascending trend. Thus, it is recommended that the government should provide with the possibility of having access to modern global technologies via making imports. In the energy sector, Iran is recommended to reduce its CO2 production compared to what is currently being produced. The speed of pollutants emissions can be reduced by raising taxes in the energy sector.

Robust controller design for a three-shaft industrial gas turbine in the infinite grid power generation

Due to the sensitivity of gas turbines’ power generation in Iran, robustness is considered as a crucial matter and the controllers play an essential role in this objective. The common controllers used in gas turbines are usually based on standard performance. Whereas, robust controllers demonstrate acceptable performance in the presence of adverse factors such as uncertainties, disturbances, and input step changes. In this study, dynamic structures and various robust control design scenarios for an MGT-30 three-shaft gas turbine have proposed. Input-output matrices have been presented based on the dynamic model structures, and a standard robust controller structure has been used to design and present transfer matrices. Four scenarios have been considered in the robust control design according to the number of control variables, uncertainties, and disturbance effects, evolutionally, respectively. [Formula: see text] and [Formula: see text] methods were used in the controller design when presenting the results of using the existing PID controller. The results show that with the increase and develop in parameters influencing the production of the actual system behavior and the controller responses improve noticeably. Finally, the fourth scenario was proposed as a scenario with more desirable robustness features than other scenarios, which provide a complete array of robust controllers.

Economic impact assessment of natural disaster with multi-criteria decision making for interdependent infrastructures

Natural disasters, such as flood, earthquake or hurricane, can cause environmental damage, infrastructural destruction, economic disruption and result in the loss of human lives. The goal of this paper is to assess vulnerability of the interdependent sectors and to determine the impact of a disaster. As part of our investigation, we explore the inoperability input–output model (IIM) to obtain ballpark estimate of losses. IIM can quantify the effect on production level and measure ripple effect of perturbation on the interdependent system by calculating the economic loss and inoperability level. Furthermore, PROMETHEE (preference ranking organization method for enrichment evaluations) is integrated with IIM, incorporating the criteria of economic system linkages, economic losses and percentage of the inoperability. It will help to analyze the effect of disaster and rank the most vulnerable sectors—based on the defined criterion. A case study is performed in Pakistan (an Asian developing country) which was hit by floods in 2011–2012, perturbing the demand in various sectors. To analyze the perturbation level and system linkages, an interdependent input–output matrix—based on the Pakistan’s economy—is constructed. Further research analysis gives perspicacity in terms of describing criticality and sensitivity of the independent economic system. It is concluded that the agriculture and service sectors have suffered with the highest inoperability level. The results also identify significant sectors of the economy after flood strikes; these sectors can be prioritized for policymaking activities to reduce the sector-specific impact in the aftermath of a catastrophic event.

Oil shocks and production network structure: Evidence from the OECD

Does the production network structure matter for the transmission of oil shocks? Using a Bayesian time-varying VAR, the paper derives the impact of oil shocks on GDP for a set of OECD economies. It further estimates various measures to characterize the production network structure based on Input–Output matrices. When the relationship between the time-varying responses of GDP to oil demand and oil supply shocks and production network characteristics is analyzed, the paper finds that measures like skewness in the in-degrees and in the out-degrees or density tend to amplify the negative impact of oil shocks on GDP. The results here are in line with the recent literature that outlines the importance of network structures for aggregate dynamics.

Adaptive iterative learning control for switched discrete-time systems with stochastic measurement noise

This paper investigates an adaptive iterative learning control (AILC) scheme for a class of switched discrete-time linear systems with stochastic measurement noise. For the case when the subsystems dynamics are unknown and the switching rule is arbitrarily fixed, the iteration-wise input-output data-based system lower triangular matrix estimation is derived by means of minimizing an objective function with a gradient-type technique. Then, the AILC is constructed in an interactive form with system matrix estimation for the switched linear systems to track the desired trajectory. Based on the derivation of the boundedness of the estimation error of system matrix, by virtue of norm theory and statistics technique, the tracking error and the covariance matrix of the tracking error are derived to be bounded, respectively. Finally, the AILC concept is extended to nonlinear systems by utilizing linearization techniques. Simulation results illustrate the validity and effectiveness of the proposed AILC schemes.

Flexibilización del modelo de insumo-producto para determinar interdependencias productivas en la ciudad fronteriza de Reynosa, Tamaulipas, 2013

Con información económica del año 2013, se sugieren estrategias de política económica regional para el municipio fronterizo de Reynosa, Tamaulipas. A partir de los modelos de Leontief y Flegg, Webber y Elliot, se construye una matriz de insumo-producto regional y su correspondiente análisis de multiplicadores. Para complementar el procedimiento, se tipifica la influencia de la actividad industrial y se brinda una visión estructural de los encadenamientos productivos siguiendo a Rasmussen. Los resultados muestran el carácter marginal de los multiplicadores de producción, empleo, remuneración de los asalariados y valor agregado en las actividades productivas no manufactureras.

Impact of pharmaceutical companies upon the economy and public finance in Poland: The Sanofi case study

The paper discusses a two-channel impact of pharmaceutical companies upon the economy and public finance. Firstly, pharmaceutical companies predominantly impact the net value added, employment, income of people employed by their suppliers and customers as well as public finance revenue in the countries where they are based. The mechanisms of such an influence are presented in the input-output matrix (input-output analysis) that shows how output from one industrial sector in the economy may become an input to another industrial sector. The input-output model was developed by Leontief and earned him the Nobel Prize. This kind of influence upon the Polish economy has been illustrated with the case study of the Sanofi company. Secondly, pharmaceutical products improve the effectiveness of medical treatment, by which they contribute to the higher standard of living and economic growth.In this part of investigation into the impact of pharmaceutical companies upon the economy the key method consists in calculating indirect costs, that is, the lost productivity (lost GDP). Non-generated GDP as well as the negative impact of diseases and the treatment thereof on public finance can be significantly reduced by using more effective pharmaceutical products. This second channel through which pharmaceutical companies exert influence on the economy has been illustrated with an example of economic consequences calculated from the social viewpoint for three gynaecological–oncology diseases. Our calculations for both channels in this exercise have led us to conclude that a pharmaceutical company positively influences its business partners and the economy while by improving the health of the population it exerts a positive impact upon the economy and public finance.

Aplicações da Matriz Insumo-Produto em análises ambientais no Brasil: uma revisão sistemática de literatura

Diversos fatores têm contribuído para o aumento da degradação ambiental do planeta. Entre eles, o aumento da população e, consequentemente, aumento da demanda por produtos e serviços, sendo considerado um dos principais fatores geradores de externalidades para o meio ambiente. De forma a identificar ferramentas para minimizar os níveis de degradação do meio ambiente, diversas iniciativas têm sido desenvolvidas de modo a descrever a relação da economia com o meio ambiente. Como sendo um destes instrumentos, a matriz insumo-produto possibilita a descrição da relação de interdependência dos setores de uma economia com o meio ambiente de forma mais específica. Neste sentido, o objetivo deste trabalho foi o de apresentar uma revisão sistemática de literatura (RSL) sobre o uso de matriz insumo-produto com enfoque a questões ambientais no Brasil. Para tanto, foi feito uma RSL em periódicos internacionais e nacionais de modo a: quantificar e analisar os estudos disponíveis que tratam da relação do meio ambiente e matriz insumo. Foi possível identificar a existência de 1.667 artigos que trabalham com a técnica de matriz insumo-produto e o meio ambiente, sendo que deste total, 19 estudos abordam essa temática para o Brasil entre os anos de 2000 a 2018.

Strategic sectors for greenhouse gas mitigation investment: assessment based upon the Brazil’s input-output matrix

Climate change is one of the biggest challenges facing the international community. The year 2017 was one of the three warmest on record and the world continues to experience extreme weather conditions. An effective mobilization of resources earmarked for key economic sectors is an important component of a strategy of any country to comply with greenhouse gases (GHG) emission reduction targets, especially Brazil, that is a top GHG emitter. This paper aims to identify these strategic economic sectors for investment to mitigate GHG emissions in Brazil. In order to do so, we estimate emission-demand elasticities of productive sectors, obtained from the Brazil’s Input-Output Matrix (IOM). In consequence, we identify those sectors with greater pollution impacts on the economy and then deserve higher priority for investment as well as mitigation policies. The paper also describes the flows and sources of climate investment and suggests that to ensure efficient outcomes policy makers should consider the role played by each different production sector. The results show the relevance of paying particular attention to the country’s productive structure and the pollution pressure it generates. From this approach, we identified that forest sector is still a key investment destination for mitigation of GHG emissions. Agriculture, transportation, and industrial sectors are also relevant to investment allocation. Confronting the results with literature and with the availability of funds, we ratified that forest and agriculture are strategic sectors for Brazil, and the sectoral approaches, classified as strong multilateralism policy architecture, are fundamental to achieve climate targets.

Short-Term Wind Speed Prediction Based on Variational Mode Decomposition and Linear–Nonlinear Combination Optimization Model

Wind power, one of renewable energy resources, is a fluctuating source of energy that prevents its further participation in the power market. To improve the stability of the wind power injected into the power grid, a short-term wind speed predicting model is proposed in this work, named VMD-P-(ARIMA, BP)-PSOLSSVM. In this model, variational mode decomposition (VMD) is combined with phase space reconstruction (P) as data processing method to determine intrinsic mode function (IMF) and its input–output matrix in the prediction model. Then, the linear model autoregressive integrated moving average model (ARIMA) and typical nonlinear model back propagation neural network (BP) are adopted to forecast each IMF separately and get the prediction of short-term wind speed by adding up the IMFs. In the final stage, particle swarm optimization least squares support vector machine (PSOLSSVM) uses the prediction results of the two separate models from previous step for the secondary prediction. For the proposed method, the PSOLSSVM employs different mathematical principles from ARIMA and BP separately, which overcome the shortcoming of using just single models. The proposed combined optimization model has been applied to two datasets with large fluctuations from a northern China wind farm to evaluate the performance. A performance comparison is conducted by comparing the error from the proposed method to six other models using single prediction techniques. The comparison result indicates the proposed combined optimization model can deliver more accurate and robust prediction than the other models; meanwhile, it means the power grid dispatching work can benefit from implementing the proposed predicting model in the system.

International R&D spillovers to the electric power industries

This article analyzes how productivity in the electric power industries (electricity, gas, steam and air condition supply) is affected through investments in R&D for OECD countries between 1995 and 2014. The accumulated R&D expenditures represent the current stock of knowledge or technology. Using a detailed input-output matrix for country-industry combinations allows us to distinguish between four types of spillovers: domestic own sector, foreign own sector as well as domestic and foreign other sector spillovers. The foreign spillovers we capture thus occur through the use of (imported) inputs from the electric power industries or from other sectors. Our estimates show that the productivity of the electric power industries is much more influenced by the transfer of embodied technology from other industries than by investments of these industries themselves. Countries with the highest stock of R&D are mainly responsible for these international technology spillovers.