Input-output Coefficients Research Articles

Footprint analysis and the incidence of emission taxes

We show that the incidence of emission taxes on consumer income classes is proportional to the footprints of their respective consumption bundles. The dimensions of the footprints are industry by product, but the literature employs industry-by-industry input-output coefficients. We rectify footprint analysis by returning to the underlying national accounts, the use and make tables. Bringing in budget shares data of the different income classes (Engel curves), we show that the carbon dioxide footprint per euro expenditure decreases with income in the Netherlands. Our result renders an emission tax regressive and thus implies a tradeoff between environmental and income policies.

A Case Study on Input–Output Analysis in the Defense Industry

Recently, the defense budget, which includes the cost of purchasing weapons, has continuously and significantly increased in South Korea. This increase, which is entirely financed by the government, has raised the issue of the socioeconomic impacts of spending on the defense industry in areas, such as production, added value and job creation. In this regard, it is necessary to more accurately measure the impact of spending on the defense industry on domestic industry, but the Bank of Korea’s industry inducement coefficient, which measures industrial spillovers, is quite limited in measuring the industry inducement impact caused by weapon production. Therefore, this study explores how to estimate the industry inducement coefficient of the production of a specific weapon by utilising the current Bank of Korea input–output table, which is focused on private industry, and applies this methodology to the estimation of the input–output coefficient of the production of a specific weapon. As a result of the analysis, the input–output coefficient of a specific weapon was estimated to be approximately 1.18 times higher than that of the products of similar industries in the private sector in terms of production, 1.03 times higher in terms of value-added and 1.03 times higher in terms of employment. This suggests that the effect of fostering domestic industry through weapon production is somewhat greater than that of private industry and proves the efficacy of government investment in this sector.

Geographical proximity and technological similarity

From a time-space perspective, we assess the effects of geographical proximity on technological convergence over time identifying proximity dimensions associated with countries’ technological similarities. We compare a time series of input-output coefficients for 66 different countries extracted from the 2021 edition of OECD Inter-Country Input-Output to verify whether nearby countries are more likely to share similar technologies. Our results reveal that geographical technological spillovers are important since closer economies tend to be more similar than distant ones. This is particularly evident for the European economies in the sample, suggesting that institutional proximity also matters for technological convergence. Over time, closer economies are becoming structurally more similar; however, this trend seems to have slowed down after the 2008–9 financial crisis. Conjectures on how informational gaps are filled in the consolidation of the databases – encountered in an environment of limited information – based on known practices of using regional and global average structures may add a layer of uncertainty to our results.

Are input-output coefficients really fixed?

ABSTRACT It is standard practice to treat input-output (I-O) technical coefficients as fixed. The coefficients are fixed when σ , the elasticity of substitution, is zero, a restriction mostly not supported by 25 years of I-O tables for Australia. We offer a simple way of allowing for variable coefficients with a CES approach. Finally, using various values of σ in CGE simulations establishes that taking coefficients as fixed has misleading economic implications.

Exploring near-linearities in price–rate of profit trajectories and the concept of effective rank in input–output matrices

In recent years, there has been a resurgence of interest in the controversies surrounding capital theory. At the heart of these debates are the empirically observed near-linearities in the price–rate of profit and wage rate of profit curves. This article posits that these near-linearities can be attributed to the low effective rank property inherent in the economy's system matrices of input–output coefficients. This suggests that a comprehensive representation of how prices evolve in response to changes in income distribution can be achieved with only a few eigenvalues and their respective eigenvectors. Furthermore, this low-dimensional system possesses the capability to capture the majority of distinctive features that characterize the input–output structure of the economy in relation to price movements.

Analysis of Algebra Structure Implementation Input-Output Applications in the Economic Field

Mathematicsi isi ai sciencei thati is usefuli ini iall fields, and is also useful in many other sciences. Mathematical models are useful, for example, in ieconomics. One of them uses matrix theory and Gauss-Jordan ielimination in iinput-output ianalysis ito studyi the inter-sectoral iinterconnectedness iof the economy. This study describes the input-output ianalysis. This isi thei implementationi ofi matrixi materiali wherei each sector usesi as inputi the output produced by the output of other sectors, on the other hand the output produced is also the input of other sectors. This research is a qualitative research (library research) with a literary approach. Data collection techniques were carried out by reviewing various books, journals, articles, information or sources deemed appropriate and relevant to the research. Content analysis is used as a data analysis technique whose purpose is to maintain research accuracy and prevent errors in data sources. This is followed by a literature review and a literature review. The results of this study are the transaction matrix, value added ratio of economic activity, technological input-output coefficient matrix, interdependence coefficient matrix and finali demandi usingi the iGauss-Jordani eliminationi method.

Optimization of a production unit of the dairy agroin-dustry: Chapingo dairy technology unit case

Objective: To evaluate the optimization level of a dairy production unit (DPU) through a mathematical programming model (MP). It is expected that by maximizing net income by at least 10%, the DPU will be more profitable than without optimized management. Design/Methodology/Approach: The analysis was carried out under the economic approach of agricultural production, taking into consideration 11 decision variables in the objective function (OF), which was subject to 20 constraints. The variables were based on the requirements of the demand for dairy by-products, using technical coefficients (input-output coefficient). Excel® Solver® was used to develop the sensitivity report and to analyze the shadow prices and reduced costs. Results: Three scenarios were modeled. Between the first and third scenario, the income increased to $58,000.00 (41.02%). Between the second and third scenario, the income increased to $63,840.00 (46.16%). Study Limitations/Implications: Dairy food processing is an important industry in the economies of the world. Findings/Conclusions: Panela cheese recorded the highest shadow price ($72.85), which indicates that the DPU should concentrate on this type of dairy product. In conclusion, the optimization of the DPU guarantees the efficient use of scarce resources and therefore generates a higher profit.

Management of Energy Recourses, Marginal Input- Output Coefficients, and Layers of Techniques: A Case Study of US Chemical Industry

The embodied technical change should reduce the cost of production of the commodity. However, price structure, wages and interest rates also will change over time. Thus if a commodity is following a fixed price regime, the adjustment of a historical input-output table to current price wage level will leaves less and less profit per unit of output. The extent of this reduction will indicate the extent of technological change. There are different approaches to the prediction of changes in input-output coefficients. The first approach, attributable to Leontief (1941) and Stone (1962), assumes that input-output matrices change over time in a “biproportional” way. The other approach is to estimate trends in individual coefficients using statistical data. Former approach is used by a number of experts, including Fontela, et al. (1970), Almon, et al. (1974) and Carter (1970). Arrow and Hoffenberg (1959), Henry (1974), Savaldson (1970, 1976), Ozaki (1976), Aujac (1972) and Buzunov (1970). These are examples of the application of the quantitative approach for forecasting input-output coefficients. Still another approach which could not get much attention for forecasting input-output coefficients, is constructing the marginal input-output coefficients [Tilanus (1967); Middelhoek (1970)]. Marginal coefficients for forecasting constructed by Tilanus and Middelhoek are based on average input-output tables, which shows that still new approach (marginal) is based on the old (average) one

Dynamic spillover capacity of R&D and digital investments in China's manufacturing industry under long-term technological progress based on the industry chain perspective

During the new era of digital-technology economics, R&D and digital investments have emerged as critical factors influencing technological change in the long term. At the same time, technological progress in industries is the fundamental cause of the R&D and digital investments spillover between industries. In order to study the dynamic spillover capacity evolutionary process generated by R&D and digital investments caused by the long-term technological change in China's manufacturing industry, this paper firstly integrates R&D and digital investments as the critical influencing factors affecting technological progress. It establishes a dynamic input-output model including endogenous technological progress, which is simulated by historical data from 2000 to 2014 to obtain the input-output coefficient matrix from 2015 to 2050. On this basis, this paper makes a rare attempt to focus the inter-industry spillover weights on the industry chain perspective to revisit and simulate the dynamic changes of inter-industry R&D and digital investments spillover capacity under the influence of long-term technological progress. As shown in the simulation results, there are significant differences in inter-industry R&D and digital investments spillover capacities among 18 manufacturing industries in China in both industry and time dimensions. The results of this study are presented in the following sections: (1) A horizontal comparison of the spillover capacity of R&D and digital investments in manufacturing industries in the same period from the industry dimension shows that the spillover capacity of R&D and digital investments between industries is dynamic because the development strategies and technological structures of industries may change over time. Hence, the position of each industry in the industry chain is not constant, and the R&D and digital investments spillover capacity between industries are also in a dynamic process. The manner and ability of an industry to generate R&D and digital investments spillover to its upstream and downstream industries may differ depending on its production location in the chain. Generally, for most upstream and near-upstream industries in China's manufacturing industry chain, the spillover capacity of R&D and digital investments of an industry to its downstream industries are greater than that to its upstream industries, and vice versa. Therefore, in order to maximize the technology spillover capacity, the corresponding technology guidance policy should be adjusted by the industry's technological progress characteristics and changes in the production location of the industry chain. (2) When comparing the spillover capacity of R&D and digital investments of each manufacturing industry longitudinally from the time dimension, the demand-pull effect of technological progress caused by R&D and digital investments of industries for their downstream industries is not as profound as the technology-push effect for their upstream industries. Hence, the fluctuations of R&D and digital investments spillover capacity generated by industries located in the upstream, near-upstream of China's manufacturing industry chain are greater than those generated by downstream, near-downstream industries. Therefore, it can be inspected that industries close to the upstream of the industry chain are more efficient in driving economic growth with their inputs in general-purpose technologies.

Inflation Targeting Model in Macroeconomics.

Empirical targeting by lowering inflation to the marginal level that causes monetary deflation and transition to depression is shown to increase the growth of the real GDP, while increasing inflation from the marginal level reduces the growth of the real GDP. The inflation is determined according to the theory of reproduction of the national economy by the mathematical function of the amount of money in circulation, foreign currency cash, interest rate, the cost of the utilized in production capital, the production input-output coefficient, and the unemployment rate. A model for regulating the economy by inflation targeting is developed, which allows the Central Bank of Ukraine to determine the target indicators for the period under consideration based on the statistical indicators of the previous period and through the nomogram of the inflation function of its arguments. The growth of the Ukrainian economy was modeled with an inflation target of four percent in 2021–2023 after the recession in 2020 caused by the coronavirus pandemic.

Agricultural land resource allocation to develop food crop commodities: lesson from Indonesia

This study estimates agricultural land resource allocation to develop food-crop commodities in order to safeguard food security in Indonesia in the middle of the coronavirus pandemic. The recommended commodities to be developed in Indonesia are corn, soybean, mungbean, peanut, and rice that are produced with advanced technology and input-output coefficient. There are five introduced scenarios namely, basic scenario, I, II, III, and IV. There are problems related to resource allocation such as limited resources, the ways of using it, and time constraints. In order to maintain and improve the comparative advantage of agricultural production as well as to broaden the agricultural activities, agricultural development is directed to increase business efficiency, improvements in agricultural science, technology, and human resource quality. The utilization of agricultural land resources should be well-planned for better development.

On the plausibility of using linear programming to trace important input–output coefficients in the framework of tolerable limits

Recent input–output (IO) literature offers original proposals on using linear programming (LP) to make ‘tolerable limits’ approach suitable for measuring the importance of IO coefficients to an economy. In this paper, I focus on one of such influential proposals presented in Tarancón et al. [(2008). A revision of the tolerable limits approach: searching for the important coefficients. Economic Systems Research, 20, 75–95]. In the theoretical part of this paper, I provide exact analytical solutions to the LP problems formulated in Tarancón et al. The main result proves that the classification of IO coefficients with respect to their importance in the sense of the LP-based indicators of Tarancón et al. does not depend on the benchmark welfare measure of interest. This fact, in turn, severely reduces practical applicability of the discussed LP-based approach to tracing important IO coefficients.

PREDICTING THE KEY PARAMETERS OF SOCIO-ECONOMIC DEVELOPMENT OF THE REPUBLIC OF BELARUS BASED ON A DYNAMIC INPUT-OUTPUT MODEL

The article provides the extended version of input-output balance and econometric model for predicting key macro-indicators of the Belarusian economy, which has been developed by the Economy Research Institute (the ERI) of the Ministry of Economy of the Republic of Belarus. Special attention has been given to such indicators as compensation of employees, gross operating surplus and gross mixed income, and other net taxes on production. All econometric models for predicting input-output coefficients, gross output by aggregates and the key elements of final use at the republican level have been overestimated and some models have been improved. Based on statistical information of the Republic of Belarus 2017–2018 predictive calculations have been performed, which have the acceptable forecast accuracy and indicate the possibility of using the proposed models in the development of forecasts and programs for the country’s socio-economic development.

Calculation of three-regions input-output coefficients, hybrid Location Quotient - Gravity Method, (Case Study: oil-rich regions, Tehran Province, and the rest national economies)

Calculation of three-regions input-output coefficients, hybrid Location Quotient - Gravity Method, (Case Study: oil-rich regions, Tehran Province, and the rest national economies)

Productivity propagation with networks transformation

We model sectoral production by cascading binary compounding processes. The sequence of processes is discovered in a self-similar hierarchical structure stylized in the economy-wide networks of production. All substitution elasticities and Hicks-neutral productivity growth are calibrated so that the general equilibrium feedbacks between all sectoral unit cost functions replicate the transformation of networks observed as a set of two temporally distant input-output coefficient matrices. This system of unit cost functions is then examined to study how idiosyncratic sectoral productivity shocks propagate into aggregate macroeconomic fluctuations in light of potential networks transformation. Additionally, we study how sectoral productivity increments propagate into the dynamic general equilibrium, thereby allowing networks transformation and ultimately producing social benefits.

Optical Spectral Filter Based on a Deep Periodic Relief Reflection Structure

A filter based on a reflecting periodic relief diffraction structure with a relief depth of greater than one half of optical wavelength is proposed. The input-output power transfer coefficient is studied versus the optical wavelength. The filter can be configured to completely suppress radiation at a specified wavelength, and the spectral characteristic can be changed due to variation in the angle of incidence of the input beam. A method for calculation of the filter parameters is proposed, and a filter that suppresses radiation at a specified wavelength and transmits radiation at another wavelength is calculated. The filter is easy-to-implement in both visible and IR spectral ranges.

Estimating employment from energy-efficiency investments

We develop a methodology for estimating the number and types of jobs that would result from investments in energy efficiency in homes, businesses, and industry. The methodology involves the development of input-output (I-O) bills of goods that characterize how energy-efficiency funds would be spent across sectors of the economy. The methodology builds on and adds greater articulation to the research conducted in prior studies of U.S. energy-efficiency policies.•The first two steps involve estimating the magnitude of investments in energy-efficient technologies and systems required to produce a unit of energy consumption reduction, and then identifying how these investments are expensed across the broad investment categories, which creates the preliminary “bills of goods” for investments in energy efficiency in homes, businesses, and industry.•The third step involves soliciting feedback on the preliminary bills of goods from experts in delivering and evaluating energy-efficiency programs, and then making necessary modifications.•In the final step we apply the input-output coefficients representing the bills of goods to estimate the direct, indirect and induced employment per million dollars of investment in energy efficiency.

Since Water transport industry has the highly relevant with other countries, the analysis of relationships with other countries gives an important data for decision making. In this study, we analyzed Inter-national economic effects through Input-Output coefficient, Production-inducement effect, and Inter-industry linkage effect from 2000 to 2014 with World Input-Output table. As a result, the proportion of Rest of World increased

Since Water transport industry has the highly relevant with other countries, the analysis of relationships with other countries gives an important data for decision making. In this study, we analyzed Inter-national economic effects through Input-Output coefficient, Production-inducement effect, and Inter-industry linkage effect from 2000 to 2014 with World Input-Output table. As a result, the proportion of Rest of World increased

The Position of Agriculture and Food Sector in V4 Countries

Input-output tables are a simple tool, used for studying the structure of economies or sectors’ demand and supply linkages. The aim of this paper is to present and compare the main characteristics of 2 selected sectors in V4 countries, namely the agriculture and food sectors. The analysis is based on the input output coefficients and multipliers, used for studying input, output and import relationships. These analyses can reveal ongoing structural changes what represents an interesting topic especially for former transition economies. The objective is to verify the similarities in the position and the development of these sectors, to examine backward and forward linkages and their strength in order to identify key sectors and to measure possible concentrations of their impacts. With accordance to the previous research and general trends, we expected certain decline of importance over the period 2000-2014, especially in terms of production, employment but also in overall effects on the whole economy. This was mostly confirmed with the exception of Polish data that point out to relatively stronger domestic position of both sectors. The presented results were obtained within the Research Project VEGA/1/0961/16

The Position of Agriculture and Food Sector in V4 Countries

Input-output tables are a simple tool, used for studying the structure of economies or sectors’ demand and supply linkages. The aim of this paper is to present and compare the main characteristics of 2 selected sectors in V4 countries, namely the agriculture and food sectors. The analysis is based on the input output coefficients and multipliers, used for studying input, output and import relationships. These analyses can reveal ongoing structural changes what represents an interesting topic especially for former transition economies. The objective is to verify the similarities in the position and the development of these sectors, to examine backward and forward linkages and their strength in order to identify key sectors and to measure possible concentrations of their impacts. With accordance to the previous research and general trends, we expected certain decline of importance over the period 2000-2014, especially in terms of production, employment but also in overall effects on the whole economy. This was mostly confirmed with the exception of Polish data that point out to relatively stronger domestic position of both sectors. The presented results were obtained within the Research Project VEGA/1/0961/16