Input-output Coefficients Research Articles

Integration of Macroeconomic Behavioural Relationships and the Input-Output Block (Romanian Modelling Experience)

The last version of the Romanian macromodel (Dobrescu 2005b) incorporates the experience accumulated through the utilisation of its previous forms - either experimental (Dobrescu 1991-1994) or operational (Dobrescu 1996-2005a). At the same time, it introduces some methodological and informational improvements. The most significant of them is the structural decomposition of economy, according to the input-output techniques. Output and absorption are divided into: a) agriculture, sylviculture, forestry, hunting, and fishing; b) mining and energy; c) manufacturing industry; d) construction; e) transport, post and communications; f) trade and services. These categories can be easily translated into the classical three-sectors classification: primary (a+b), secondary (c+d), and tertiary (e+f). Due to the relatively advanced stage of the transitional processes in Romania, the behavioural functions were modelled - as much as possible - by the standard relationships. Besides, unlike the previous versions (that used statistical series beginning with 1980) the present one is based exclusively on information regarding the period 1989-2004. Since the input-output tables are defined yearly, the model contains only annual indicators. They are expressed in denominated local currency (RON). The export, import, and exchange rate series were transformed in Euro. When there were several informational sources for the same indicator, the data extracted or derived from national accounts have been adopted. The statistical series are relatively short and often fractured (because of the transforming processes of transition). Although, it is known that ADF test of stationarity does not offer reliable results in the case of limited number of observations, generally the series satisfying it were used. The simplest regression methods were also preferred. The structural breaks in evolution of some series have been dealt by the inclusion of dummies. Obviously, all these circumstances weaken the stability of econometric coefficients that must be continuously updated. The first two chapters of the paper characterise the main macroeconomic behavioural relationships and input-output coefficients. The third one discusses a possible scenario for the Romanian economy during 2005-2010. A set of simulations is presented in the final part of the paper; these reveal some operational features of the macromodel.

ON THE PARAMETERIZATION OF TECHNIQUES FOR REPRESENTING REGIONAL ECONOMIC STRUCTURES

This paper is concerned with two parameterized methods of regionalising input–output coefficients: the Flegg et al. Location Quotient (FLQ) and its augmented version (AFLQ). For applying the two techniques, a parameter δ has to be estimated. In this regard, the paper faces two matters that are still open in the literature: the existence of a range of δ that can be used in different regions and the estimation of the most appropriate value of δ. For this aim, a Monte Carlo simulation has been carried out in order to generate ‘true’ multiregional I-O tables randomly. From the simulation, analyses based on probability distributions and regression were also carried out. Finally, these simulation results have been compared with those of an empirical case. Results confirm that there is actually a range of values of δ within which the best δ is more likely to fall. For the FLQ, this range is centred on 0.3 with an associated probability of 33% (if the width of the range is set at 0.1), whereas, for the AFLQ, the relevant range is between 0.3 and 0.4 with a probability by 38%. Finally, this paper provided a way to estimate the best δ for a given region, without knowing the relevant and detailed economic structure at sectoral level.

CO2배출비용을 고려한 발전소의 연료교체 경제성에 대한 연구

일본 도야코에서 2008년 7월 열린 G8 정상회의에서 2050년까지 전세계 온실가스 배출량을 절반으로 줄이는 장기 목표를 추진하는 방안이 논의되었다. 우리나라도 2013년부터 기후협약 규제가 거의 확실시 되고 있다. 화석연료의 연소로 대부분의 전력을 생산하는 발전산업은 우리나라 CO₂ 대기배출량의 20[%] 이상을 차지하고 있다. 발전소의 화석연료의 소모와 이에 따른 CO₂ 대기배출 규제는 갈수록 엄격해 질 전망이며 전력생산단가에 크게 영향을 끼칠 것이다. 본 논문은 발전소의 연료교체 검토시 CO₂ 배출비용을 감안하는 간단한 경제성 검토를 수행하였다. 중유 전소 발전소인 D 발전소가 LNG로 연료전환을 고려할 경우, 발전비용이 같아지는 ton당 CO₂ 배출비용, 즉, LNG중유 연료교체의 손익분기점에 해당하는 ton당 CO₂ 배출비용을 계산하는 방법과 예제를 제시하였다. 이를 위하여 D발전소의 성능시험 결과 얻어진 입출력 특성계수를 이용하였다.

FRAGMENTATION AND CLUSTERING IN VERTICALLY LINKED INDUSTRIES*

ABSTRACT This paper models the location of two vertically related firms in a low labor cost country and in a country with a large market. The upstream industry is more labor intensive than the downstream industry. We find that spatial fragmentation occurs for low values of the input-output coefficient and intermediate values of the transport rate, particularly if the countries are very asymmetric in size. Otherwise, we obtain agglomeration either in the low cost country (when the transport rate is low) or in the large market (when the transport rate is high). Multiple agglomerated equilibria arise when the transport cost of the intermediate good is significant.

An Input-output Analysis of Sources of Growth and Key Sectors in Malaysia

The paper examines the sources of growth and key sectors of Malaysia’s economy over 1978-2000 using a decomposition method and Rasmussen degree of dispersion within the input-output (IO) framework. The model uses three comparable IO tables for 1978, 1991 and 2000 as the main data sources and accounts for output changes from a demand side perspective. The chosen structural decomposition analysis (SDA) based on the comparison between two IO tables, allows us to decompose each sector’s and industry’s output growth. It decomposes output growth of each sector to domestic demand expansion, export demand expansion, import substitution of final goods, import substitution of intermediate goods, and changes in IO coefficients. The analysis by sub periods, 1978-1991 and 1991-2000 show that there was a switch in the role of domestic-demand and export-demand expansion. The constituent factors that contribute positively to change in the period, 1978-1991 are mostly domestic demand expansion (63.35%) and export demand expansion (33.33%). However in the second sub period, 1991-2000, export demand expansion increased by 12.43% and domestic demand expansion decreased to 48.11%. Taking the whole 1978-2000, domestic demand expansion appears to have been the major source of output growth, contributing about 82%, followed by export demand expansion 62%. Combining the source of growth and key sector through backward linkages, the study revealed that most of the sectors induced its supplying production strongly for domestic market.

Evolutionary micro-dynamics and changes in the economic structure

The paper aims to account for the empirical stylized facts related to changes in sectoral structures that have led to the growth of services in most advanced countries over recent decades. A growth model with evolutionary micro–founded structural change is developed, which formalizes the role of technical change and changes in intermediate demand as they affect the evolution of the sectoral composition of the economy and macro-economic growth. The simulated results are based on the use of the actual data, including Input–Output coefficients in the case of Germany. Three scenarios are identified, which account for the effects of a set of key parameters on changes in the structure of the economy.

화력발전소의 CO2배출량 및 배출비용 함수산정과 5모선 전력계통 적용사례

1997년 교토 기후협약이 체결되었고, 세계는 지금 지구온난화 문제로 CO₂전쟁을 치르고 있다. 우리나라도 2013년부터 기후협약 규제가 거의 확실시 되고 있다. 화석연료의 연소로 대부분의 전력을 생산하는 발전산업은 우리나라 CO₂ 대기배출량의 20[%] 이상을 차지하고 있다. 발전소의 화석연료의 소모와 이에 따른 CO₂ 대기배출 규제는 갈수록 엄격해 질 전망이며 전력생산단가에 크게 영향을 끼칠 것이다. 본 논문은 화력발전소의 입출력 특성계수를 이용하여 발전출력에 대한 CO₂ 대기배출비용 함수를 유도하는 방법과 이를 전력계통의 운용에 반영하는 방안을 제시한다. 모형계통의 시뮬레이션을 통하여 CO₂ 배출량과 CO₂ 대기배출비용을 감안한 전력계통 최적운전 연산 사례를 도시하였다.

Analysing Logistics Flows in Industrial Clusters Using an Enterprise Input-Output Model

Industrial clusters provide an interesting example of local systems of production that are facing global competition. The firms’ processes acquire raw materials, convert them into final products, and deliver final products to retailers. Short and long range transfers of materials and energy are becoming crucial for clusters’ competitiveness. Logistics activities have a particular importance for geographic clusters where production activities and residences are remarkably diffused and this results in high mobility and environmental problems. The coordination of transport demand implies a new integration and organization of logistics not only to reduce costs and enhance management control, but also to reduce their impact on the environment.In the paper, we propose the use of an enterprise input-output model to analyse logistics flows in order to support coordination policy at the level of the whole industrial cluster.First, logistics flows between firms’ processes are modelled aggregating similar processes to create a complete account for logistics flows in the industrial cluster. Successively, considering the disaggregated representation of processes, different coordination policies for logistics flows ranging from hierarchy to market are examined and modelled. The effects of such policies on input-output coefficients of the industrial cluster model and on logistics performance are evaluated. A case study related to an Italian cluster producing leather upholstery is considered and different coordination policies are compared also in terms of impact on productivity and environment.

The Extraction of Technical Coefficients from Input and Output Data

Presumably, input-output coefficients reflect technology, and these coefficients measure the input requirements per unit of product. This concept has been extended to consumption theory, where it models expenditure shares. Input-output coefficients are extracted from the national accounts of an economy, by taking average proportions between inputs and outputs. Since the latter represent all sorts of inefficiencies, this practice blurs the measurement of technology. Input requirements are better measured by minimal proportions between inputs and outputs. This approach separates the measurement of technology from that of productive efficiency.

LINEAR PROGRAMMING MODELS WITH CHANGEABLE PARAMETERS — THEORETICAL ANALYSIS ON "TAKING LOSS AT THE ORDERING TIME AND MAKING PROFIT AT THE DELIVERY TIME"

Corporate competence sets can be expanded through capital investment and be dynamically changed overtime, which can explain the phenomenon of "taking loss at the ordering time and making profit at the time of delivery". Such phenomenon has existed in practice for a long time, but there are no mathematical model that can explain it adequately. This paper utilizes multiple criteria and multiple constraint levels linear programming (MC2LP) model and its extended techniques to explore the linear programming models with changeable parameters. The parameters include: unit profit, available resources, and input-output coefficients of production function. With those parameters changed with capital investment and/or time, we study how to find dynamic best solutions to make "taking loss at the ordering time and making profit at the time of delivery" feasible. For more general cases we also sketch a generalized mathematical programming model with changeable parameters and control variables.

화력발전소 입출력 특성계수를 이용한 순시 발전출력 대비 CO2 대기배출량 계산

1997년 지구온난화 문제를 해결하기 위해 교토 기후협약이 체결되었고, 우리나라도 2013년부터 기후협약 규제가 거의 확실시 되고 있다. 우리나라 온실가스 배출량은 연간 약6억 톤이며, 그 중 CO2가 5억 톤이다. 특히 화석연료의 연소로 대부분의 전력을 생산하는 발전 산업은 우리나라 CO2 배출량의 20[%] 이상을 차지하고 있다. 따라서 발전소의 전력생산에 따른 화석연료의 소모량과 이에 따른 CO2 배출량을 mnnitoring하는 것이 매우 중요해졌다. 본 논문은 발전소의 성능시험 결과 얻어지는 입출력 특성계수와 IPCC(Intergovrnmental Panel on Climate Change)의 온실가스 추계 방법론을 이용하여 순시 발전출력에 따른 CO2 대기배출량을 계산하는 방법을 제시하였다. 4모선 모형계통의 시물레이션을 통하여 전력계통의 조류계산과 발전소별 CO2 배출량을 연립 연산하는 예를 도시하였다.

Technological change in energy systems: Learning curves, logistic curves and input–output coefficients

Learning curves have recently been widely adopted in climate-economy models to incorporate endogenous change of energy technologies, replacing the conventional assumption of an autonomous energy efficiency improvement. However, there has been little consideration of the credibility of the learning curve. The current trend that many important energy and climate change policy analyses rely on the learning curve means that it is of great importance to critically examine the basis for learning curves. Here, we analyse the use of learning curves in energy technology, usually implemented as a simple power function. We find that the learning curve cannot separate the effects of price and technological change, cannot reflect continuous and qualitative change of both conventional and emerging energy technologies, cannot help to determine the time paths of technological investment, and misses the central role of R&D activity in driving technological change. We argue that a logistic curve of improving performance modified to include R&D activity as a driving variable can better describe the cost reductions in energy technologies. Furthermore, we demonstrate that the top-down Leontief technology can incorporate the bottom-up technologies that improve along either the learning curve or the logistic curve, through changing input–output coefficients. An application to UK wind power illustrates that the logistic curve fits the observed data better and implies greater potential for cost reduction than the learning curve does.

Impacts of Aggregation on Relative Performances of Nonsurvey Updating Techniques And Intertemporal Stability of Input–Output Coefficients

In many instances, and for variety of reasons, input–output researchers are compelled to both employ mechanical techniques to update older survey-based tables as well as using more aggregated ones. This combination, however, gives rise to several concerns. The present paper is an attempt to investigate two such questions. First, the effects of aggregation on the accuracy ranking of selected updating methods, and second, the effects of aggregation on intertemporal stability of the input–output coefficients. To probe these issues, three updating methods were selected. These methods are NAIVE or constant coefficient hypothesis, RAS or biproportional method, and LaGrangian optimization technique. Two survey-based tables from the former Soviet Union along with the selected updating techniques are used to generate updated target year’s direct and inverse transaction matrices at four aggregation levels. Comparison of the resultant estimates at these four levels of aggregation with their counterparts in the actual benchmark table reveals that a higher level of aggregation neither affects the rankings of the updating methods nor does it universally and unequivocally leads to a higher degree of intertemporal stability of input–output coefficients.

Modeling Basic Industries in the Australian Stocks and Flows Framework

The Australian stocks and flows framework (ASFF) is a tool for establishing a coherent historical picture of the Australian physical economy and for testing long‐term future scenarios (up to 2050 or even 2100). These scenarios can be used to investigate the long‐term physical consequences of current and future choices affecting the physical dimensions of sustainability. In this article we describe the methodology for and construction of a key component of ASFF: a dynamic physical input‐output model of material flows in the basic industries.The materials model in ASFF describes physical flows and their transformation by industrial processes. The model's structure permits scenario analysis of long‐term technological change by permitting time‐varying input‐output coefficients and vintage models of capital stocks. As a consequence, the model contains a large number of parameters, which can be left at default settings or adjusted as the modeler sees fit, in order to simulate the widest possible range of physically realizable scenarios. The materials model is built using a methodology that integrates bottom‐up process analysis with top‐down statistics on material and energy flows. We present some examples showing how the materials model has been implemented to model Australian heavy industries. Several possibilities for further developing the materials model are also described.

Does the appointment of judges increase the output of the judiciary?

We use panel data on Israeli courts to estimate the “production function” for case dispositions. Our results show that the number of case dispositions is independent of the number of serving judges, and that “productivity”, as measured by completed cases per judge, varies directly with the caseload per judge. These results suggest that the productivity of judges is endogenous; for the same caseload judges complete more cases under pressure, and complete less when new judges are appointed. They also suggest that the practice of determining the number of judges by fixed “Leontieff” input–output coefficients is not appropriate.

A dynamic model to analyse the bio-technical and socio-economic interactions in dairy farming systems on the Réunion Island

This paper presents a framework that permits an integrated analysis of a complex livestock system in which biophysical, technical, socio-economic and policy components intervene. The main aims were to analyse the investment decisions and management strategy in the livestock system, and to simulate its future evolution under exogenous shocks (agricultural policies, technical opportunity). A multidisciplinary approach was used, based on a dynamic linear programming model that integrates technical and socio-economic constraints, policy making, technology choice, opportunities and farmer's objectives. This approach postulates that farmers make their decisions according to knowl- edge of the relation between production factors, the amount of output obtained and the level of unit costs of each production activity and future market prices. A technical matrix, containing a collection of relevant technical coefficients that describe the production functions (input-output coefficients), was built on the basis of observations of local farming systems. These coefficients and the opportu- nities offered to each farm type to produce goods subject to constraints are expressed in linear equa- tions and are introduced in the model types. This modelling approach was used in the case of the dairy farming system on the Reunion Island. Applied to six dairy farm types, this approach showed the correct representation of the observed behaviour by the model, and the extreme sensitiveness of most farming incomes to agricultural policies and especially to public support. These models are currently operational and may be used to accompany decision-makers, especially dairy cooperative leaders, in their considerations on the management of farms.

Input Coefficient Change Using Biproportional Econometric Adjustment Functions

This paper deals with the issue of updating input-output (I-O) coefficients within a large-scale disaggregated econometric macro-model of the Austrian economy. Capturing the changes in input coefficients over time is an important issue in I-O modelling due to a lack of recent benchmark I-O tables in most countries. Different approaches for updating these coefficients can be found in the literature, such as adjusting input coefficients 'along the row' and variable input coefficients 'along the column' stemming from factor input equations derived from production or cost functions. This paper combines these two approaches, yielding a biproportional method. For the adjustment, 'along the column' econometric factor input functions are used to derive a sum of non-energy intermediate inputs. For the adjustment 'along the row' the starting point is a set of adjustment functions described in the literature: special emphasis is placed on econometric specification and 'cointegration accounting'.

New Developments in the Use of Location Quotients to Estimate Regional Input–Output Coefficients and Multipliers

Tohmo T. (2004) New developments in the use of location quotients to estimate regional input–output coefficients and multipliers, Reg. Studies 38, 43–54. This study compares the survey-based regional input–output coefficients and production multipliers published by Statistics Finland, 2000, with estimates obtained by applying location quotients (LQs) to national data. The consequences of using alternative adjustment formulae, the ‘SLQ, CILQ and FLQ’ are illustrated by an input–output model constructed for the Keski-Pohjanmaa (K-P) region. The results indicate that the SLQ and CILQ both produce highly misleading regional input–output coefficients and multipliers. These adjustment formulae are clearly not good enough for the purposes of making local policy and regional planning. The FLQ formula (β=1) yields much better regional input–output coefficients and multipliers than the SLQ and CILQ. The FLQ gives very good estimates for regional multipliers in nearly all industries. The difference between the multipliers generated by the FLQ and the survey-based K-P regional multipliers is on average about −0·3%. The multipliers for the K-P region are typically much lower than for Finland as a whole, indicating that the economic structure of the K-P region is dependent on that of other regions. Hence there is a need to make proper allowance for interregional trade. In the case of the K-P region, the FLQ with β=1 was able to offset the tendency of the CILQ to generate excessively large regional multipliers.

Uncertainty in Integrated Regional Models

This paper examines the nature of uncertainty in integrated econometric+input–output (ECIO) regional models. We focus on three sources of uncertainty: (a) econometric model parameter uncertainty; (b) econometric disturbance term uncertainty; and (c) input–output coefficient uncertainty. Through a series of Monte Carlo simulations we analyse the relative importance of each component as well as the question of how their interaction may propagate through the integrated model to affect the distributions of the endogenous variables. Our results suggest that there is no simple answer to the question of which source of uncertainty is most important in an integrated model. Instead, that answer is conditioned upon the focus of the analysis and whether the industry specific or macro level variables are of central concerns.

The Construction of Input–Output Coefficients Matrices in an Axiomatic Context: Some Further Considerations

Kop Jansen & ten Raa (1990) established a purely theoretical solution to the problem of selecting a model for the construction of coefficients on the basis of make and use tables. In an axiomatic context, they singled out the so-called commodity technology model as the best one according to some desirable properties. The aim of this paper is to delineate the restrictions on the relevant data sets that ensure fulfilment of the desirable properties by other models used by statistical offices.