Dynamic Input-output Model Research Articles

The problem of digitalization of the dynamic input-output model

Subject. The article addresses the digitalization of the dynamic model of inter industry balance. Objectives. We focus on developing our own statistical research base for input-output analysis, structural forecasting, sustainability, economic dynamics and economic growth. Mathematically, the study is formalized by the Cauchy problem for ordinary differential equations. Methods. The methodology components include theoretical and practical bases of the systems, statistical, input-output, and structural dynamic analysis. Results. Based on official statistics, we solved the problem of digitalization of the dynamic model of input-output balance, written in the form of a system of differential equations. For the first time, this model was transferred from a set of purely theoretical structures to a class of computable models. We developed a sequence of coordinated actions and calculations, which serve as a methodology for the said transfer. We also devised and presented the elements of our own statistical research base. Conclusions. The quantitative measurement of the dynamic inter-industry model in the form of a system of differential equations opens up broad perspectives on the sustainability of macroeconomics, its structural readiness for expanded reproduction, i.e. economic growth. The model can be used both independently and in combination with equilibrium and other agent-oriented models.

Input-output dynamic model for optimal environmental pollution control

This paper describes the allocation of a wastewater treatment fund within a region based on a dynamic input-output model. Considering the complexity of the input-output process, many indeterminate factors must be included in the model. For example, with the aging of machines, an unexpected loss will be caused by the retention of raw materials during an operation; this can be realistically considered as a random variable, because of the sufficiently large amount of historical data. By contrast, actions such as a temporary transfer or inexperienced operators can only be regard as uncertain variables, because of a lack of historical data. First, the pollution control model is formulated in an uncertain environment by including both human uncertainty and objective randomness. Second, an optimal control model subject to an uncertain random singular system is established; this model can be transformed into an equivalent optimization problem. To solve such a problem, recurrence equations are presented based on Bellman’s principle, and these were successfully applied to address the optimal control problem in two special cases. Moreover, two algorithms are formulated for solving the pollution control problem. Finally, the optimal distribution strategies of the pollution control fund used to control the emissions of COD and NH3-H, which are two indicators of wastewater in China, were obtained through the proposed algorithms.

Forecasting Accelerated Renovation of Fixed Capital Assets in Russia Using a Dynamic Input-Output Model

The article analyzes the state of fixed capital in Russia and evaluates the necessary parameters for the accelerated replacement of obsolete fixed assets. Using the dynamic input-output model (DIOM) three variants of the forecast for the development of the Russian economy for 2019–2024 are developed.

Return of the capital coefficients matrix

A core ingredient of post-disaster input–output recovery models is the reconstruction of lost production capacity. Therefore, one would expect a set of models endowed with capital coefficients matrices to be available for analysis. However, this is not the case, possibly due to earlier negative experiences with such models. Nevertheless, in this paper, we aim to show that there is a class of problems that can be addressed successfully with a dynamic input–output model with a fully functioning capital coefficients matrix. We put forward that if reconstruction is tightly planned, investment and therewith gross output essentially become pre-determined. This also means that traditional final demand becomes an endogenous residual, with the model being transformed into a distribution and allocation model. We begin with a reordering of variables and equations as proposed in Leontief’s dynamic inverse, and then move on directly to the newly proposed model. Suggestions for further work are given.

ВИКОРИСТАННЯ МЕТОДУ ТЕОРІЇ ЗБУРЕНЬ ДЛЯ ДОСЛІДЖЕННЯ ДИНАМІЧНИХ РІВНЯНЬ МІЖГАЛУЗЕВОГО БАЛАНСУ

Економічна система охоплює параметри і характеристики суспільного виробництва, розподілу, обміну та споживання матеріальних благ. В економічній системі вибір і формування як структури, так і способу функціонування є задачами управління, що забезпечують динаміку соціально-економічного розвитку. У структурі системи управління можна виділити: об'єкт управління – це безпосередній пристрій, агрегат, підсистема загальної системи, в якій реалізується мета функціонування всієї системи; управляюча система – представляє собою орган управління (суб'єкт управління), що фіксує параметри об'єкта управління і виробляє керуючі впливи на об'єкт управління; обернений зв'язок – це об'єкт, підсистема, за допомогою якої реалізується вплив управляючої системи на керований об'єкт. Ці елементи разом утворюють замкнену систему управління. Задачі управління економічною системою погано структуровані, і не завжди модель може бути побудована однозначним способом. Це означає, що цілі функціонування багатьох економічних систем не завжди можуть бути чітко сформульовані. Задача управління такою системою полягає в тому, щоб прийняти найкраще рішення для цієї системи. Одним з ефективних методів дослідження економічної динаміки як в теоретичному, так і в прикладному аспекті є динамічні моделі витрати-випуск (моделі міжгалузевого балансу). Математичні залежності між величиною капітальних вкладень і приростом продукції є основою побудови різних варіантів динамічних моделей міжгалузевого балансу. Відмінною рисою динамічних моделей міжгалузевого балансу є виділення виробничих капіталовкладень (інвестицій) зі складу кінцевої продукції і вивчення їх впливу на зростання обсягу виробництва. В роботі складається та аналізується нелінійний варіант динамічної моделі Леонтьєва, розглядається можливість дослідження динамічних рівнянь міжгалузевого балансу при виникненні збурень в елементах матриць прямих матеріальних затрат та внутрішніх інвестицій. За результатами дослідження зроблені висновки про вплив збурень на матриці внутрішніх інвестицій і матеріальних витрат.

Almost “very strong” multilane turnpike effect in a non‑stationary Gale economy with a temporary von Neumann equilibrium and price constraints

Mathematical models of economic dynamics and growth are usually expressed in terms of differential equations/inclusions (in the case of continuous time) or difference equations/inclusions (if discrete time is assumed).3 This class of models includes von Neumann-Leontief-Gale type dynamic input-output models to which the paper refers. The paper focuses on the turnpike stability of optimal growth processes in a Gale non-stationary economy with discrete time in the neighbourhood of von Neumann dynamic equilibrium states (so-called growth equilibrium). The paper refers to Panek (2019, 2020) and shows an intermediate result between the strong and very strong turnpike theorem in the non-stationary Gale economy with changing technology assuming that the prices of temporary equilibrium in such an economy (so-called von Neumann prices) do not change rapidly. The aim of the paper is to bring mathematical proof that the introduction of these assumptions making the model more realistic does not change its asymptotic (turnpike-like) properties.

The Dynamic Input-Output Model of Distribution Network Upgrading Project Under the Background of Electric Internet of Things

China is promoting the construction of electric internet of things, and a large part of the fixed asset investment in the power grid is the investment in the upgrading of the distribution network. The economic benefits of investment are related to the sustainable development of power grid companies. At present, the Chinese government is reforming transmission and distribution tariff, and the economic benefits of power grid infrastructure investment are facing greater uncertainty. This paper studies the life cycle cost of the distribution network upgrading project from construction to decommissioning and the electricity revenue for the entire operation period. The dynamic input-output model of the distribution network upgrading project is established under the background of electric internet of things. An empirical analysis is conducted in combination with the case study. Through load forecasting and cost calculation, the input and output indicators of the project are obtained, which verifies the validity and accuracy of the model.

A study of degrowth paths based on the von Neumann equilibrium model

Abstract This paper revisits the von Neumann equilibrium model from a degrowth perspective. Degrowth can be either planned or autonomous based on voluntary simplicity (VS), characterized by voluntary constraints on the private consumptions. Any share of the working population is allowed to limit their private consumptions or ecological footprint. Degrowth means a lower economic growth rate as well as reductions in the usage of materials and fossil energy; however, when the economy cannot fit within the biophysical boundary despite such reductions, degrowth can also mean a deliberate transition towards lesser and cleaner production of a smaller number of goods. Taking ecological boundaries into consideration may thus switch the direction of an economy from growth to degrowth. Degrowth is consistent with economic equilibrium in the dynamic input-output model. Degrowth equilibrium results when a critical mass of the population prioritizes diminishing the ecological deficit over increasing the output levels. Green growth can take place during degrowth. While the economy gradually shrinks, the interest (profit) rate in macroeconomic equilibrium is negative due to the conservation target (excessive consumption has negative value to VS-type agents). Degrowing private consumptions implies less work, more leisure and better quality of the environment, improving social welfare. Degrowth can be advanced by adopting a more cooperative production system or by imposing high ecological taxes. The equilibrium model yields an argument for basic income as a means of supporting welfare during degrowth and of compensating for unpaid work. The open economy version of the model shows reduced scope for intra-industry trade between similar countries.

Оценка влияния национальных проектов на развитие экономики России с использованием динамической межотраслевой модели

<span>В статье предпринята попытка оценки влияния выполнения национальных проектов на динамику макроэкономических и отраслевых показателей экономики России в 2019–2024 г. Прогнозные расчеты выполнены на основе динамической межотраслевой модели (ДММ). Информационной базой для нее послужила информация Правительства РФ о национальных проектах и данные таблиц «Затраты</span><span class="myHorizontalScaleForEmDashSpaceBefore"> </span><span>–</span><span class="myHorizontalScaleForEmDashSpaceAfter"> </span><span>Выпуск» за 2015 г. В предположениях прогноза и задаваемых экзогенных показателях нашли отражение основные параметры реализуемых нацпроектов. Использование ДММ позволило оценить динамический мультипликативный эффект от связанных с ними дополнительных расходов для внутреннего валового продукта России (ежегодный и за весь период в целом), показать влияние этих проектов на отраслевую структуру производства. Показано, что реализация национальных проектов позволит ускорить экономический рост в России.</span>

EXPERIENCE OF THE INPUT-OUTPUT MODELS APPLICATION TO THE MOLDOVAN ECONOMY

The main goal of this article is to present an overview of the input-output models which have been applied to Moldovan economy development study. We examined: static input-output model, dynamic input-output model restricted by limited energy resources, and the Markov chain approach based on the input-output tables. All these models have been examined using statistic data referring to the input-output table, constructed on the base of aggregated branches of the Moldovan economy. Static and dynamic optimization models were formulated, simulation calculation was done and analysed. Input-output table balancing problem was solved using RAS method. For dynamic model matrix of the investment coefficients was constructed. The emphasis was putt on the problem of applying the theory of Markov chain for examination of the 19 and 16 branches in the framework of the input-output model for Republic of Moldova. A square exchange matrix of order has been constructed. Every branch was considered as one of the states of the Markov chain with states. We introduced a new -th absorption state so that the examined matrix became of the order . The obtained transition matrix – probabilities matrix has been used for forecasting

Dual Forecasting Algorithm for Technological Structural Matrices in Dynamic Input-Output Models

Based on the global Krotov successive improvement method, we propose a dual computational algorithm for a discrete optimal control problem corresponding to a convex large-scale quadratic programming problem with a separable functional that arises in the prediction of the direct costs (structural) matrix in dynamic input-output models. With decomposition, we are able to use a special form of the constraint matrix to reduce the problem dimension.

Economic Model-Based Controller Design Framework for Hydraulic Fracturing To Optimize Shale Gas Production and Water Usage

As water issues associated with hydraulic fracturing have received much attention, several optimization approaches have been developed for effective water management. However, most of them have not considered pumping schedules for hydraulic fracturing, which determine the productivity of a shale well as well as the total amount of freshwater required. Because of this, a novel model-based control framework is proposed for hydraulic fracturing to maximize the net profit from shale gas development which simultaneously minimizes the total cost associated with water management. The framework is as follows: initially a reduced-order model and a Kalman filter are developed based on the simulation data generated from a high-fidelity hydraulic fracturing model to correlate the pumping schedule and the final fracture geometry. Then, a numerical reservoir simulator and mixed-integer nonlinear programming model are used to generate two maps describing the revenue from selling shale gas produced and cost from managing wastewater recovered, respectively. Finally, by applying a data-based dynamic input–output model to connect the two maps, an economic model predictive control system is formulated. The proposed control framework enables 62% of the generated wastewater to be reused through the application of thermal membrane distillation technology in the treatment process and results in a 11% reduction in overall freshwater consumption, while maintaining the productivity of a shale well at its theoretical maximum.

Complex Modeling of the Economic Systems Stability

Our work is devoted to the problem of the economic systems stability analysis. At the same time, we call stable those economies that demonstrate growth and expansion up to the limits guaranteed by the modern level of technological development of mankind. Such growth in terms of “production”, “profit”, “business cost” should be harmoniously combined with the welfare growth and fundamental “confidence in the future” of the people.The objectives of the study are: 1) the analysis of the factors that are difficult for modeling both in general and in the study of the economic stability problems in particular; 2) the development of options to improve the validity, effectiveness and practical value of the equilibrium models use for the options of economic policy, its results and prospects mapping. Substantiation of expediency of stability, economic and welfare growth modeling on the basis of a set of computable General equilibrium models, and dynamic input-output models; 3) the development of mathematical algorithm for optimization of economic systems’ own dynamic properties, auxiliary functions of the transient processes quality simulating investment activity in economy as a necessary condition for the economic growth.

THE INPUT-OUTPUT MODEL: ONE OF THE BASIC ELEMENTS OF INFORMATION SUPPORT FOR THE WORK OF REGIONAL SITUATIONAL CENTERS

Goal. Modern situational centers are focused on the preparation of evidence-based management decisions of the executive authorities of the federal and regional levels. Their work is aimed not only at making decisions in emergency situations but also at questions of forecasting, planning and implementing socio-economic trends and development programs. Modification of input-output (IO) models is an actual task for these purposes. Materials and methods. The article proposes a modification of the IO model, focused on the simultaneous modeling of the production process and the dynamics of the consumption sphere, as well as taking into account the influence of exogenous macroeconomic parameters. A classification of models is given; methods for the identification of their parameters on the basis of publicly available global and domestic databases are described. Results. We developed methods for customizing models for solving specific problems. The model varies depending on the consideration of various macroeconomic parameters and the degree of detail of the basic balance ratios. Linear continuous and discrete models allow solving investment management problems. Variation of exogenous parameters leads to non-linear dynamic IO models. Conclusion. It is shown that the proposed approach allows providing information support to public administration associated with the analysis and correction of socio-economic trends, as well as the development of the necessary software. At the same time, its successful implementation is possible only if there are relevant statistical databases on regional economies and information infrastructure.

Unraveling economic and environmental implications of cutting overcapacity of industries: A city-level empirical simulation with input-output approach

On a way towards transition to greener and more intensive development patterns, many Chinese cities are ambitiously prompting cutting overcapacity as a primary task of supply-side reform. However, the impacts of cutting overcapacity of industries on economic development and environmental quality still remain unrevealed clearly. In this study, a dynamic input-output simulation model is developed by integrating supply and demand balances of material and value with industrial capacity and applied to Tangshan City, which is typically implementing cutting overcapacity against four key sectors (oil processing and coking, cement, iron and steel, and power and heat). Three scenarios are set for analyzing changes in capacity and pollutant (SO2, NOx and particulate matter) emission mitigation during 2017–2025 through mutual comparisons. Changes in capacity of four key sectors as well as gross regional product are simulated. Industrial structure will be reshaped with most notable changes in service industry and iron and steel industry. Critical industrial chains are traced for manifesting to what extent cutting overcapacity will influence the sectors closely interacted with the key sectors. Remarkable mitigation of emissions and concentration contribution can be contributed by cutting overcapacity with accumulative mitigated emissions of the pollutants as 0.48, 1.09 and 0.79 Mt, respectively. As a first attempt on combining input-output analysis with research on industrial capacity and on investigating environmental impacts of cutting overcapacity, this study is expected to provide reference to pertinent policy-making with regard to sound capacity regulation of industries.

Будет ли новый экономический прорыв в России?

<span>В статье рассматриваются возможности значительного ускорения экономического роста в России в 2019–2024 гг. Проводится сравнение динамики национального ВВП с показателями крупнейших мировых экономик в период 1999–2017 гг. С помощью динамической межотраслевой модели выполнено обоснование трех вариантов развития российской экономики</span><span class="myHorizontalScaleForEmDashSpaceBefore"> </span><span>–</span><span class="myHorizontalScaleForEmDashSpaceAfter"> </span><span>базового, оптимистического и пессимистического. Показано, что для осуществления нового экономического рывка в 2019–2024 гг. ВВП России должен увеличиваться среднегодовым темпом 4,0–5,5%, при этом среднегодовой темп прироста инвестиций в основной капитал должен находиться в интервале 8–10%. Приводится перечень мер государственной политики, способствующих ускорению экономического роста.</span>

Economic Impact of the Passage of the Medical Marijuana Law in the State of Florida

In 2016, Florida Governor signed House Bill 307 that expanded the State's Right to Try Act to include medical marijuana. However, two years after this initiative, little is known about the economic impact of legal medical marijuana use (MMU) on the State of Florida. The goal of this research is to forecast the total economic impact arising from MMU on Florida, from 2017 to 2025, using a dynamic input-output model. Input data for the model were obtained from the Florida Office of Medical Marijuana Use. The economic impact of MMU was measured in terms of gross state product, disposable personal income, migration, labor force, employment, and salaries and wages. The legalization of medical marijuana in Florida is associated with an increase in all the economic indicators in 2017. A positive trend for these indicators is observed from 2017 to 2025 except for migration with a negative trend starting in 2019.

Dynamic Input-Output Model with a Human Capital Block Applied to Forecasting of the Russian Economy

The article deals with the methodological issues of data preparation for the human capital block of the dynamic input-output model of the Russian economy and analyzes the results of a long-term forecast prepared based on this model.

Перспективы развития экономики Республики Бурятия

<span>В статье исследуется развитие экономики Республики Бурятия в 2007–2017 гг., приводятся и анализируются результаты прогнозных расчетов и развития на период до 2021 г. в двух вариантах</span><span class="myHorizontalScaleForEmDashSpaceBefore"> </span><span>–</span><span class="myHorizontalScaleForEmDashSpaceAfter"> </span><span>базовом и оптимистическом. Прогнозные расчеты выполнены с использованием разработанной авторами динамической межотраслевой модели экономики Республики Бурятия с нечеткими параметрами. В работе показано, что при благоприятных макроэкономических условиях и резком росте инвестиций в основной капитал возможно существенное ускорение экономического роста в Бурятии. Обсуждаются конкретные проекты, которые позволят ускорить экономический рост в республике.</span>

A control-theoretic system identification framework and a real-time closed-loop clinical simulation testbed for electrical brain stimulation

Objective. Closed-loop electrical brain stimulation systems may enable a precisely-tailored treatment for neurological and neuropsychiatric disorders by controlling the stimulation based on neural activity feedback in real time. Developing model-based closed-loop systems requires a principled system identification framework to quantify the effect of input stimulation on output neural activity by learning an input-output (IO) dynamic model from data. Further, developing these systems needs a realistic clinical simulation testbed to design and validate the closed-loop controllers derived from the IO models before testing in human patients. Approach. First, we design a control-theoretic system identification framework to build dynamic IO models for neural activity that are amenable to closed-loop control design. To enable tractable model-based control, we use a data-driven linear state-space IO model that characterizes the effect of input on neural activity in terms of a low-dimensional hidden neural state. To learn the model parameters, we design a novel input waveform—a pulse train modulated by stochastic binary noise (BN) parameters—that we show is optimal for collecting informative IO datasets in system identification and conforms to clinical safety requirements. Second, we further extend this waveform to a generalized BN (GBN)-modulated waveform to reduce the required system identification time. Third, to enable extensive testing of system identification and closed-loop control, we develop a real-time closed-loop clinical hardware-in-the-loop (HIL) simulation testbed using the microelectrode recording and stimulation device, which incorporates stochastic noises, unknown disturbances and stimulation artifacts. Using this testbed, we implement both the system identification and the closed-loop controller by taking control of mood in depression as an example. Results. Testbed simulation results show that the closed-loop controller designed from IO models identified with the BN-modulated waveform achieves tight control, and performs similar to a controller that knows the true IO model of neural activity. When system identification time is limited, performance is further improved using the GBN-modulated waveform. Significance. The system identification framework with the new BN-modulated waveform and the clinical HIL simulation testbed can help develop future model-based closed-loop electrical brain stimulation systems for treatment of neurological and neuropsychiatric disorders.