Dynamic Input-output Model Research Articles

Tracking Control of the Dynamic Input-Output Economic System Based on Data Fusion

In recent years, under the background of stable economic operation, people's research on economic systems has become increasingly popular. The dynamic input-output model reflects the change and development process of the input-output relationship of the economic system over a period of time. The main purpose of tracking control is to design a suitable controller so that the output of the control system can track the output of the reference system as much as possible. In the economic system, data is an important factor. Based on this, this paper mainly studies the tracking control of dynamic input-output economic system based on data fusion. This research takes the data fusion of the dynamic input-output economic system as the starting point and takes the optimal control and tracking of the economic system as the research object of this research. Based on data fusion technology, a new dynamic input-output economic system tracking and control is proposed. This paper studies the finite-time optimal tracking control of linear systems. Through numerical examples, comparing the finite-time and infinite-time optimal control simulation results, it is proved that the algorithm can achieve good tracking control. Experimental data shows that the optimal and suboptimal performance indicators for a limited time are 0.7729412 and 1.5687310, respectively. Therefore, compared with the infinite-time optimal control, the performance loss and the final tracking error of the suboptimal control proposed in this study are reduced.

A Study on the Decay Model of Multi-Block Taxi Travel Demand under the Influence of Major Urban Public Health Events.

A sudden major public health event is likely to have a negative impact on public transport travel for residents, with public travel modes such as the metro and conventional buses experiencing varying degrees of decline in patronage. As a complement to public transport, taxi travel will suffer the same impact. Land use and population density among various functional blocks in a city are different, and therefore their changing rates in taxi travel demand are varied. This paper reveals the taxi travel demand correlations between urban blocks and then constructs a taxi travel demand decay model based on the Dynamic Input-Output Inoperability Model (DIIM) to simulate the decay degree of taxi travel demand in each block. When a major public health event occurs, the residential panic levels in different functional blocks may vary. It results in variable changing speeds of residential travel demand in each block. Based on this assumption, we use the intensity of travel demand as a correlation strength factor between blocks, and equate it with the technical coefficient in the DIIM model. We also define other variables to serve in model construction. These variables include the decay degree of travel demand intensity, residential travel willingness, coefficient of travel demand decay, derivative coefficient of travel demand interdependency, and demand perturbation coefficient. Lastly, we select a central area of Ningbo as the study area, and use taxi travel data in Ningbo during the COVID-19 pandemic of 2020 as input, simulate taxi travel demand dynamics, and analyze the accuracy and sensitivity of the model parameters. The relative errors between the five types of blocks and the actual decay of travel demand intensity are 8.3%, 3.8%, 8.7%, 5.5%, and 5.3%, respectively, which can basically match the actual situation, proving the validity of the model. The results of the study reveal the pattern of taxi travel demand decay among various blocks after major public health events. It provides methodological reference for decision makers to understand the development trend of multi-block taxi travel demand, so as to help form effective emergency plans for different blocks.

The optimal industrial carbon tax for China under carbon intensity constraints: a dynamic input-output optimization model.

To reduce carbon emissions, the Chinese government is considering introducing a differentiated industrial carbon tax on enterprises outside the carbon trading market in the future. An efficient carbon tax must consider not only how carbon taxes impact the current economy but also how the size of the tax should be adjusted across time due to external changes. To calculate the optimal industrial carbon tax for China which is subject to certain constraints, this paper investigates the economic and environmental effects of four possible industrial carbon tax rate models under carbon intensity constraints from 2021 to 2030 by a dynamic input–output optimization model. The results show that the dynamic tax rate model leads to larger fluctuations in GDP growth than the other tax models, with a low initial tax rate in the beginning and a high tax rate exceeding ¥180/t in 2030. Second, a large quantity of capital stock is distributed across the energy-intensive industries, which leads the existing capital investment structure to be path-dependent. This offsets the performance of carbon taxes. Third, indirect energy-intensive industries such as construction and transport are insensitive to the industrial carbon tax. Finally, comparing the impacts of the four tax rate models, the optimal industrial carbon tax for China is found to be a fixed differentiated tax rate, in which energy-intensive sectors are taxed ¥75/t and low-carbon sectors are taxed ¥50/t.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-022-19162-6.

Simulation Analysis of Economic Damages and Recovery after a Mount Fuji Eruption: Using a Dynamic Input-Output Model and Hypothetical Scenarios

Simulation Analysis of Economic Damages and Recovery after a Mount Fuji Eruption: Using a Dynamic Input-Output Model and Hypothetical Scenarios

Structural inertia of economic systems

Systemic inertia forms a transdisciplinary field of studies, which includes interests of natural sciences, technical studies, humanitarian studies, socio-economic studies, etc. Economic science mainly relied on the methods of economic theory and philosophy to analyze this phenomenon. The globality of this subject impeded the formalization of research, and numerical interpretation of inertia were limited to the introduction of a coefficient in an economic and mathematical model. At the same time, the opportunity of getting numerical values of structural inertia in the industry coordinates was provided by basic dynamic input-output balance model, written as a system of basic differential equations. This model’s capital coefficients matrix (according to V. Leontief) is non-singular and can be called the matrix of interindustry inertia. Its elements have time dimensionality. This research presents the methodology for calculating the matrix. Its dimensionality is equal to the dimensionality of the matrix of the formation of the output of goods and services published by ROSSTAT with the interval of two years. This methodology consists of verifiable sequence of algebraic transformations within the input-output methodology with the specified matrix. This research represents the inertia, related to the processes of formation of basic stock, and the inertia of the formation of the gross value added of Russian economy. The high practical importance of the research consists in the development and demonstration of the economic and mathematical apparatus for contrastive analysis of structural dynamic properties of different economies when they are modeled in the coordinates of the same industries.

Structural inertia of economic systems

Systemic inertia forms a transdisciplinary field of studies, which includes interests of natural sciences, technical studies, humanitarian studies, socio-economic studies, etc. Economic science mainly relied on the methods of economic theory and philosophy to analyze this phenomenon. The globality of this subject impeded the formalization of research, and numerical interpretation of inertia were limited to the introduction of a coefficient in an economic and mathematical model. At the same time, the opportunity of getting numerical values of structural inertia in the industry coordinates was provided by basic dynamic input-output balance model, written as a system of basic differential equations. This model’s capital coefficients matrix (according to V. Leontief) is non-singular and can be called the matrix of interindustry inertia. Its elements have time dimensionality. This research presents the methodology for calculating the matrix. Its dimensionality is equal to the dimensionality of the matrix of the formation of the output of goods and services published by ROSSTAT with the interval of two years. This methodology consists of verifiable sequence of algebraic transformations within the input-output methodology with the specified matrix. This research represents the inertia, related to the processes of formation of basic stock, and the inertia of the formation of the gross value added of Russian economy. The high practical importance of the research consists in the development and demonstration of the economic and mathematical apparatus for contrastive analysis of structural dynamic properties of different economies when they are modeled in the coordinates of the same industries.

Energy consumption analysis and saving of buildings based on static and dynamic input-output models

With the increase of building area, energy consumption of building and carbon dioxide (CO2) emissions have been increased. Reducing the energy consumption of buildings has an enormous impact on the sustainable development of the world economy and social. Therefore, this paper proposes a novel energy consumption analysis and saving method of the building based on static and dynamic input-output models. The input-output based data envelopment analysis (DEA) is used to analyze the energy consumption of the building statically. Then the slack variables obtained by the DEA are used to improve efficiency values of ineffective days in months of buildings. Moreover, the total factor productivity (TFP) with technical efficiency (EFFCH), technical progress (TECHCH), pure technical efficiency (PECH), scale efficiency (SECH) and the total factor productivity change (TFPCH) of the building is dynamically analyzed by the Malmquist index. Finally, the static and dynamic energy consumption analysis and saving method is used to improve the energy efficiency of the building. Furthermore, when the technical progress by 1%, the total factor productivity change of the building can be improved by 1.042%.

Analysis of the impact of dynamic economic resilience on post-disaster recovery “secondary shock” and sustainable improvement of system performance

Quantitative measuring disaster resilience especially dynamic economic resilience (DER) belongs to a frontier research in the past decades, which can effectively improve post-disaster economic recovery effects, reducing post-disaster loss. However, DER focuses more on the overall shape changes of recovery path, two features that commonly appear in the dynamic change process of recovery curve are also worth evaluating separately: the “secondary shock” caused by adverse factors during the recovery process and sustainable improvement of economic output at the end of recovery. Therefore, we adopt a dynamic input–output model that integrates capital damage and affected people and apply it to an extreme flood in 2016, Wuhan City, China, building the relationship between 7 recovery actions (rescue funds) and changes of two features, analyzing the impact of resilience on the dynamic recovery path features through 6 characteristic variables constructed in this paper. Results show that (1) economic resilience increases from no to actual action, the dropping rate caused by “secondary shock” decreases 30.4%, and Wuhan’s economic output has achieved an improvement in sustainability of 0.088% compared to the pre-disaster level, which contributes permanently to reducing vulnerability to future disasters. (2) only 21.81% (compared to the actual scenario) of the rescue funds is needed to support 30% reduction action plus 0.02% sustainable improvement. But to support the 50% recovery action, 78.92% of the rescue funds is needed. This paper aims to provide a new perspective for the refined dynamic assessment of resilience and to prove the role of resilience in promoting short-term post-disaster recovery and long-term sustainable development.

Assessing indirect economic losses of landslides along highways

Landslides along highways not only induce direct losses related to cost of replacement, repair or maintenance due to physical damage, but also induce indirect losses due to reduction in production in different sectors in an economic system. In this study, a method is suggested to assess the indirect losses of landslides along highways, where the impact of landslides on the transportation network is evaluated through the gravity model, and the output losses of different sectors are computed based on the dynamic input–output model. The suggested method is used to assess the indirect losses of landslides that occur along highways related to Yingxiu Town, Sichuan Province, China, which is the epicenter of the 2008 great Wenchuan earthquake. It is found that the impact of a landslide hazard on different sectors is not the same depending on their dependence relationship with the transportation sector. The indirect losses of a landslide increase as the repair time increases and decrease as the transportation network becomes more robust. Also, the location of a landslide will affect the caused indirect losses, and the indirect losses will increase as the transportation network is attacked by more landslides. The suggested method provides a useful instrument for estimating the indirect losses of landslides along highways, which were seldom addressed in previous studies.

Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation.

Direct electrical stimulation can modulate the activity of brain networks for the treatment of several neurological and neuropsychiatric disorders and for restoring lost function. However, precise neuromodulation in an individual requires the accurate modelling and prediction of the effects of stimulation on the activity of their large-scale brain networks. Here, we report the development of dynamic input-output models that predict multiregional dynamics of brain networks in response to temporally varying patterns of ongoing microstimulation. In experiments with two awake rhesus macaques, we show that the activities of brain networks are modulated by changes in both stimulation amplitude and frequency, that they exhibit damping and oscillatory response dynamics, and that variabilities in prediction accuracy and in estimated response strength across brain regions can be explained by an at-rest functional connectivity measure computed without stimulation. Input-output models of brain dynamics may enable precise neuromodulation for the treatment of disease and facilitate the investigation of the functional organization of large-scale brain networks.

Dynamic Input Output Analysis: Carbon, Water and Ecological Hierarchy

As the main component of greenhouse gases, excessive carbon emissions are responsible for global climate change and anomalies. Carbon emission metabolism is essential for alleviating climate changes globally. Here, a dynamic input-output model is developed for analyzing carbon emission metabolism and ecological hierarchy. Direct and indirect carbon emissions are evaluated, and mutual relationships between various sectors are explored. The innovation of this research is summarized as follows: firstly, for carbon emission, the competition relationships reveal good interactions in terms of emission reduction while mutualism relationship provides effective pathways to mitigate carbon emissions between pairwise sectors simultaneously. Moreover, analysis of direct and indirect carbon emissions could help to extract embodied sectors with large emissions and identify whether the sectors should adjust their production structure or upgrade the clean combustion technology. In addition, ecological hierarchy analysis would help to identify key sectors lacking driving or pulling force during study period. It provides a new insight into the potential sectors which play an important role in the emission reduction. Results show that carbon emissions mainly concentrated in electricity-generation, manufacturing, and transportation sectors. In Guangdong province, upgrading the clean combustion technology in electric power generation and energy extraction sectors would drive other sectors to cut emissions and adjusting the production structure of the construction sector also contribute to achieve this goal. Tertiary industry is not sufficiently promoting Guangdong’s economic development, and therefore plays a restrictive role in the current economy. Results could help decision makers to develop emission mitigation policies.

In and out of Lockdown: Propagation of Supply and Demand Shocks in a Dynamic Input-Output Model

Economic shocks due to COVID-19 were exceptional in their severity, suddenness and heterogeneity across industries. To study the upstream and downstream propagation of these industry-specific demand and supply shocks, we build a dynamic input-output model inspired by previous work on the economic response to natural disasters. We argue that standard production functions, at least in their most parsimonious parametrizations, are not adequate to model input substitutability in the context of COVID-19 shocks. We use a survey of industry analysts to evaluate, for each industry, which inputs were absolutely necessary for production over a short time period. We calibrate our model on the UK economy and study the economic effects of the lockdown that was imposed at the end of March and gradually released in May. Looking back at predictions that we released in May, we show that the model predicted aggregate dynamics very well, and sectoral dynamics to a large extent. We discuss the relative extent to which the model's dynamics and performance was due to the choice of the production function or the choice of an exogenous shock scenario. To further explore the behavior of the model, we use simpler scenarios with only demand or supply shocks, and find that popular metrics used to predict a priori the impact of shocks, such as output multipliers, are only mildly useful.

Problems in Developing a Comprehensive Toolkit for Macro-economic, Inter-regional, Inter-sectoral Analysis and Forecasting

The study reviews approaches to macro-economic and macro-territorial modelling presented in international and Russian economic publications. We focus on opportunities to improve forecasting the development of economic system in Russia at the macro-economic, inter-sectoral and inter-regional levels. We described dynamic macro-economic, inter-sectoral and inter- regional models developed in the Institute of Economics and Industrial Engineering of the Siberian Branch of the Russian Academy of Sciences (IEIE SB RAS). We analyse more in details three complex models proposed in IEIE SB RAS: CAISI (comprehensive analysis of inter-sectoral information), SRNES (synthesis of regional and national economic systems) and CSNES (coordination of sectoral and national economic solutions). We consider theoretical foundations of the complex models and their application in analysing and forecasting economic system development at various levels. The three complex models are based on different basic models that influence their development. IEIE SB RAS has been developing a two-level system of forecasting models, which combines advantages of dynamic stochastic general equilibrium models and dynamic input-output models applied in the CAISI system. The paper describes theoretical foundations of the SRNES system, whose latest versions are premised on the general equilibrium and cooperative games theories. Then, we characterised the most developed elements of the complex model CSNES, which has the CSNES-TEK subsystem used in forecasting developments in the fuel and energy industry of Russia’s territories and SIBARP (balance calculation system for the future). The conclusion outlines directions for further research on improving the methods of macro-economic, inter-regional, and inter-sectoral forecasting based on harmonisation of analytical and forecast calculations performed using the CAISI, SRNES and CSNES systems. The results of forecast calculations using the two-level system of macro-level models can be applied in the complex models SRNES and CSNES to ensure coordination between the forecasts of socio-economic development of the Asian part of Russia and projected dynamics of macro-indicators.

Optimal control for uncertain discrete-time singular systems under expected value criterion

Optimal control problems governed by two different types of uncertain discrete-time singular systems are investigated under expected value criterion. The objective function including uncertain variables is optimized with the help of expected value method provided that the singular systems are both regular and impulse-free. At first, based on the principle of dynamic programming, a recurrence equation is derived to simplify an optimal control model for a class of uncertain discrete-time singular systems. After that, according to uncertainty theory and the recurrence equation, two kinds of optimal control problems subject to an uncertain linear singular system and an uncertain singular system with quadratic input variables are considered in order, and the optimal solutions are both presented by accurate expressions. A numerical example and a dynamic input-output model are settled to illustrate the effectiveness of the results obtained.

Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models

Storm surge disaster is one of the biggest threats to coastal areas. Over the years, it has brought serious losses to the economy and environment of China’s coastal areas. In this paper, Guangdong Province is taken as the research object to evaluate the damage caused by storm surge disasters. First of all, regarding the three-industry classification standards of the National Bureau of Statistics, combined with the storm surge disaster assessment index system, the 10-sector storm surge disaster loss input-output table is compiled and analyzed. Secondly, the indirect economic losses of storm surge disasters between 2007–2017 are determined by calculating the direct and indirect consumption coefficients. Thirdly, based on the static input-output model, considering the time factor, the dynamic input-output model of storm surge disaster assessment is established to calculate the cumulative output loss under different recovery periods (30 days, 90 days, 120 days, 180 days, 360 days). The results indicate that: (1) the losses, after a storm surge, in the agricultural economy have the greatest impact on the manufacturing sector, and conversely, they have less effect on the science, education and health service sectors; as well as the construction sector; (2) taking the industry with the biggest loss ratio as an example, the recovery of damaged industries is relatively rapid in the early stage and tends to be stable in the later stage of recovery; (3) the total output loss calculated using the static input-output model is greater than that computed using the dynamic input-output model. Researching the assessment of the direct and indirect loss due to storm surge disasters is of great value and practical significance for the scientific and rational planning of the country’s production layout, the maintenance of social and economic stability and the protection of life and property.

Prospects for the Economic Development of the Republic of Buryatia

ABSTRACT The article analyzes the development of the economy of the Republic of Buryatia spanning 2007–2017 and provides two forecast analyses of the republic’s economic development until 2021: the baseline forecast and the optimistic forecast. To generate the forecasts the authors used a dynamic input–output model of the Buryat economy that includes fuzzy parameters. It is shown that under favorable macroeconomic conditions and a sharp increase in fixed capital investment, it is possible to significantly accelerate economic growth in Buryatia. Specific projects that will accelerate economic growth in the republic are discussed.

Macroeconomic evaluation of an impact that a production increase project of a large oil company may have on development of the Russian economy

The paper reviews an approach to systemic evaluation of projects implemented in the oil industry in connection with preferences granted for paying the resource extraction tax. The project under consideration concerns a set of solutions aimed at increased oil production by a large oil company (hereinafter the Company). The approach put forward by the authors of the paper is based on the input-output table analysis that allows demonstrating and appraising commercial effect of proposed solutions as well as tracing the full chain of inter-industry collaboration and the impact of the project on the Russian economy at large. Calculations have been made on the basis of the dynamic input-output model of the Russian economy developed at the Institute of Economics and Industrial Engineering of the Siberian Branch of the Russian Academy of Science). This approach, among other things, makes it possible to estimate those additional revenue inflows to the consolidated budget of Russian Federation that relate in particular to indirect effects from implementation of the project. An important feature of the proposed approach is consideration of dynamic economic processes that take place not only in the oil industry but also industries adjacent to it and with due regard for interaction between industries in the Russian economy as a whole.

On the Economic Effects of a Res Local Industry Deployment in Morocco: A Case of Study Defining Scenarios from a Survey to Stakeholders

The aim of this article is to simulate the economic impact on Gross Domestic Product (GDP) and employment of renewable energy sources investment in Morocco over the next 40 years. In this sense, several potential scenarios of energy component evolution have been used based on the results of a specific survey to sector stakeholders. We obtain accurate results, avoiding speculative/theoretical assumptions in terms of scenario design. As usual in the sector, a Dynamic Input–Output Model (DI–O) is used to estimate the direct and indirect effects of such a large investment and, avoiding the criticism of this type of model in the context of long-term simulations, the alternative of de Arce et al. (2012) is used. In this framework, substantial results derive from the three scenarios considered: the increase in Moroccan GDP as a result of this investment could be around 1.2–1.7 points and, on average, 42,000 new jobs could be created.

David Hawkins and the making of the Hawkins-Simon conditions

The Hawkins-Simon conditions, which are necessary and sufficient for the viability of input–output systems, are described in many encyclopedias, textbooks and papers, but always without historical details about the philosopher David Hawkins. The rich literature on the history of input–output economics has neglected Hawkins, probably because he spent only a few years among the economists. My paper fills this gap. By using the relevant archival material on Hawkins, Simon, and Leontief, I correct and expand some scarce remarks on Hawkins by Simon and Samuelson. I discuss Hawkins’s three remarkable contributions to economics. First, Hawkins’s dynamic input–output model in Econometrica in 1948 scooped Leontief. Second, I show how the correspondence between Hawkins and Simon created their famous joint note in Econometrica in 1949. Third, an overlooked chapter in Hawkins’s 1964 book The Language of Nature discussed the commodity values of commodities, generalizing Marx’s labour values and the Technocrats's energy values.

Richard Cantillon’s stabilizing market dynamics

ABSTRACT1 We consider a dynamic input output model that represents important aspects of Richard Cantillon’s discussion of economic structure and market dynamics. Merchants and inventories determine prices that diverge from (longer run) equilibrium. We contrast this stable formulation of price determination with an unstable benchmark specification in which variations in mercantile inventories play no role. Appreciated the stabilising properties of classical dynamics but did not isolate the influence of inventory behaviour. We briefly consider the role of inventories in macroeconomics, and note that balance sheet effects have rendered credit dislocations considerably more persistent than they were in Cantillon’s day.