REGIONAL WATER FOOTPRINTS OF THE YANGTZE RIVER: AN INTERREGIONAL INPUT–OUTPUT APPROACH

Recently, researchers have applied the multi-regional input–output (MRIO) approach to water footprint (WF) analysis. The concept of interregional input–output (R-MRIO) was developed to analyse regional issues. Researchers have concentrated on the development of global or international input–output (N-MRIO) tables. Using the N-MRIO and the R-MRIO approach allows the study of global and regional issues, respectively. The WF is an indicator influenced by trade among nations and regions. However, the treatment of imports in an R-MRIO approach differs in whether international imports are separated or combined. We evaluate the effects of the difference between these models and discuss policy implications for the Yangtze River, China. The WF calculated using the combined type model is 11% larger than that by the separated type model. This difference can be ascribed to international imports, mainly internal consumption and interregional trade. We find that this difference affects social equity in water-abundant areas.     

ANALYSING THE STRUCTURE OF THE ECONOMY USING PHYSICAL INPUT–OUTPUT TABLES

Analyses using physical input–output tables (PIOTs) are key to understanding the physical metabolism of economies, since they relate production to the generation of emissions and use of resources. Two methods have been developed to calculate the primary resources and emissions associated with a given final demand. However, one of these alters the PIOT, revealing different technical coefficients and Leontief inverse matrices. Which method should be used for structural analysis? In this paper, I compare both methods, explain the structural differences between them and illustrate the latter through a backward linkage analysis. I find that only one method is suited to the analysis of the physical structure of the economy, since it comprehends both the production of goods and associated emissions. The method is identified as a new model capable of tracing by-products as final outputs. Finally, I generalise both methods to analyse PIOTs including several emission types.     

EMPIRICAL ESTIMATION OF NON-LINEAR INPUT–OUTPUT MODELS: AN ENTROPY ECONOMETRICS APPROACH

Despite theoretical advances, non-linear input–output models have been empirically applied only to a limited extent. This is mainly due to the fact that the number of parameters to be estimated is much higher than the number of available data points. Taking advantage of the recent proliferation of input–output databases and by applying an estimation strategy that relies on entropy econometrics, this paper suggests a way to estimate the parameters that characterize non-linear relationships between inputs and output. This non-linear modelling allows for considering time-specific input coefficients, instead of fixed ones. Several types of multipliers can be derived from this non-linear model, and the proposed generalized maximum entropy (GME) estimator allows estimating them from time series or cross-sectional datasets of input–output tables. The proposed GME technique is illustrated by means of an empirical application that estimates the parameters that characterize a non-linear input–output model for the Spanish economy over the period 1995–2011.     

AN INPUT–OUTPUT STUDY OF THE SINGAPORE INFORMATION SECTOR

The development and use of information and communication technologies is one of the key drivers of the ‘knowledge economy.’ In this paper, we investigate the impact of information technology on the output growth of the Singapore economy using the input–output framework. The input–output framework allows us to understand the impact of information sector in an integrated framework in terms of its linkages to the manufacturing and service sectors. In particular, we adopt the input–output approach to shed light on both production and diffusion activities of the information sector on the Singapore economy. The results indicate that the ICT sector provided the key linkages for the expansion of high-value added manufacturing activities and electronics export for the Singapore economy.     

TESTING ASSUMPTIONS MADE IN THE CONSTRUCTION OF INPUT–OUTPUT TABLES

Product input–output (IO) tables are mainly constructed on the basis of product and/or industry technology assumptions. The choice is not trivial and deserves empirical analysis using input and output data at the level of establishments. This paper offers input–output compilers econometric tests to facilitate the construction of tailored hybrid technology-based product IO tables. We provide weighted likelihood ratios of the product and industry technology assumptions. Although the proposed econometric tests are aimed to be used ex ante, we construct four variants of hybrid technology-based product IO tables using establishment data from Andalusia (Spain) and contrast them to the official product IO table and the pure product and industry technology-based tables. Our econometric tests are not valid for industry IO tables.     

INPUT–OUTPUT ANALYSIS: THE NEXT 25 YEARS

This year marks the 25th anniversary of the International Input–Output Association and the 25th volume of Economic Systems Research. To celebrate this anniversary, a group of eight experts provide their views on the future of input–output. Looking forward, they foresee progress in terms of data collections, methods, theory testing, and focus and scope.     

AGGREGATION VERSUS DISAGGREGATION IN INPUT–OUTPUT ANALYSIS OF THE ENVIRONMENT

Analysts carrying out input–output analyses of environmental issues are often plagued by environmental and input–output data existing in different classifications, with environmentally sensitive sectors sometimes being aggregated in the economic input–output database. In principle there are two alternatives for dealing with such misalignment: either environmental data have to be aggregated into the input–output classification, which entails an undesirable loss of information, or input–output data have to be disaggregated based on fragmentary information. In this article, I show that disaggregation of input–output data, even if based on few real data points, is superior to aggregating environmental data in determining input–output multipliers. This is especially true if the disaggregated sectors are heterogeneous with respect to their economic and environmental characteristics. The results of this work may help analysts in understanding that disaggregation based on even a small amount of proxy information can improve the accuracy of input–output multipliers significantly. Perhaps, these results will also provide encouragement for preferring model disaggregation to aggregation in future work.     

CONSTRUCTING AN ENVIRONMENTALLY-EXTENDED MULTI-REGIONAL INPUT–OUTPUT TABLE USING THE GTAP DATABASE

The use of Multi-Regional Input–Output Analysis (MRIOA) for understanding global environmental problems is growing rapidly. Renewed interest in MRIOA has led to several large research projects focused on constructing detailed and accurate MRIOTs. However, very few researchers have made use of the already available and regularly updated database produced by the Global Trade Analysis Project (GTAP). We demonstrate and discuss how the GTAP database can be converted into an MRIOT without the need for additional balancing. An illustrative example uses the GTAP-MRIO to reallocate carbon dioxide emissions from producing to consuming countries. We suggest that an MRIOT that treats international transport exogenously is adequate until more reliable data on international transport margins and emissions are available. To focus resources and refine methods, a concerted research effort is needed to compare the results of the GTAP-MRIO model with the new MRIO datasets under development.     

OPTIMIZING PRODUCTION IN THE GREEK ECONOMY: EXPLORING THE INTERACTION BETWEEN GREENHOUSE GAS EMISSIONS AND SOLID WASTE VIA INPUT–OUTPUT ANALYSIS

We explore an input–output based framework for optimizing production in the Greek economy, under constraints relating to energy use, final demand, greenhouse gas emissions and solid waste. Using empirical data, we consider the effects on the maximum attainable gross value of production when imposing various pollution abatement targets. Our results quantify those effects as well as the magnitude of economic sacrifices required to achieve environmental goals, in a series of policy scenarios of practical importance. Because air pollution and solid waste are not produced independently of one another, we identify the settings in which it is meaningful to institute a separate policy for mitigating each pollutant, versus those in which only one pollutant needs to be actively addressed. The scenarios considered here represent a range of options that could be available to policy makers, depending on the country's international commitments and the effects on economic and environmental variables.     

COMPLEMENTARITY IN INPUT–OUTPUT ANALYSIS AND STOCHASTICS

The complementarity between the quantity and value systems of input–output analysis is shown to be the basis of the complementarity problem approach to computable general equilibrium. The numerical superiority of the latter to the linear programming approach facilitates stochastic analysis of input–output scenarios. For the example where Kyoto targets are underachieved to uncertain degrees, confidence intervals are derived for the associated consumption reductions.     

REFLECTIONS ON THE INOPERABILITY INPUT–OUTPUT MODEL

We argue that the inoperability input–output model is a straightforward – albeit potentially very relevant – application of the standard input–output model. In addition, we propose two less standard input–output approaches as alternatives to take into consideration when analyzing the effects of disasters or disruptions.     

THE COMPILATION OF CHINA'S INTERREGIONAL INPUT–OUTPUT MODEL 2002

The increasing economic interaction among various regions in China makes the construction of an interregional input–output table relevant for economic studies. This paper elaborates the model compilation procedure of the China Interregional Input–output model 2002. The key features of the model compilation include: (1) using representative commodities to estimate the interregional commodity flows of the primary industries; (2) adopting functions to estimate the decreasing interregional transportation of manufacturing sectors in relation to distance and (3) selecting appropriate indicators to estimate the interregional commodity flows of non-material sectors. This study is an initial attempt in interregional input–output modelling and might be helpful for economic studies at the levels of micro-regions.     

ESTIMATION OF SYMMETRIC INPUT–OUTPUT TABLES: AN EXTENSION TO BOHLIN AND WIDELL

This paper presents two optimisation models for use in the production of symmetric input–output tables (SIOTs) based on data contained within supply-use tables (SUTs). The first model produces commodity-by-commodity SIOTs derived from the selection of appropriate technology assumptions, while the second produces industry-by-industry SIOTs derived through the selection of appropriate sales structure assumptions. Both models address the problem of negative coefficients and also permit the use of rectangular SUTs as base input data. Additionally, this paper explores the development of a ‘comprehensive model’ enabling production of both commodity-by-commodity and industry-by-industry SIOTs that are conceptually and mathematically consistent.     

CONSTRUCTION OF MULTI-REGIONAL INPUT–OUTPUT TABLES USING THE CHARM METHOD

Subnational multi-regional input–output tables (IOT) are important tools for studying interregional socio-economic and/or environmental interrelations that help to address a wide range of current societal, ecological and economic challenges. However, the lack of subnational input–output data is a major obstacle which leads to a wide use of non-survey methods. Like other non-survey methods, the cross-hauling adjusted regionalization method (CHARM) was originally developed for the construction of single-regional IOT. In this paper, we extend CHARM to the case of bi- and multi-regional IOT. We find that the original CHARM formula has two limitations that are also of great importance for the single-regional case: First, cross-hauling in interregional trade is implicitly set to zero and, second, accounting balances may be violated owing to structural differences between the regional and national economies. We present a modified formula addressing these issues and examine its performance in terms of a case study.     

THE ‘REST OF THE WORLD’ – ESTIMATING THE ECONOMIC STRUCTURE OF MISSING REGIONS IN GLOBAL MULTI-REGIONAL INPUT–OUTPUT TABLES

Incomplete data for the economic structure of numerous countries hamper the compilation of global multi-regional input–output (MRIO) tables. By themselves, most of these countries are of only limited importance for the global economy and incumbent environmental issues. Hence, in most recent global MRIO tables these countries are either roughly estimated or summarised in one rest of the world (RoW) region. Combining a wide range of countries, this RoW region may play a significant role in global economic and environmental accounts. We conceptualise the importance of RoW in several environmental footprint accounts and present algorithms to estimate the structure of RoW. The approach utilises the information of the economic structure within known parts of the MRIO table to estimate the unknown structure. Using this method, global warming potential and employment footprints remain stable irrespective of the chosen initial estimates, whereas natural land use footprints and individual product impacts vary significantly.     

CONSTRUCTION,STABILITY AND PREDICTABILITY OF AN INPUT–OUTPUT TIME-SERIES FOR AUSTRALIA

This paper documents the development of a time series of Australian input?output tables. It describes the construction techniques employed in order to overcome the major issues encountered. Environmentally important processes were delineated using a range of detailed commodity data, thus expanding the original tables from roughly 100 industries into a temporally consistent 344 industries. Data confidentiality and inconsistency were overcome using an iterative constrained optimisation method called KRAS???a recent modification of RAS (Lenzen et al. 2006; 2007; 2009). The article concludes by analysing the stability of input?output coefficients over time similar to work in Dietzenbacher and Hoen (2006). The issue of stability of coefficients and multipliers was investigated under the Leontief and Ghosh models of supply/demand. Finally, the predictability of the models was examined under updated final demand or primary inputs and over varying time scales.     

INTEGRATING A HOUSEHOLD DEMAND SYSTEM IN THE INPUT–OUTPUT FRAMEWORK. METHODOLOGICAL ASPECTS AND MODELLING IMPLICATIONS

In this paper we argue that an accurate representation of household consumption behaviour is central to the analysis and comparison of policy interventions addressing sustainable consumption. Therefore, we propose to extend an input–output model with a specific household consumption model, at the core of which is a system of equations explaining the allocation of the households' overall expenditure across different purposes, such as buying food, the consumption of fuel for heating or electricity for cooling, education of children or travelling in terms of total expenditure and relative prices. This paper shows that the integration of a specific module for household consumption in a standard input–output model is an improvement for the analysis of the policies aimed at altering consumer behaviour.     

THE EXTENDED ECONOMETRIC INPUT–OUTPUT MODEL WITH HETEROGENEOUS HOUSEHOLD DEMAND SYSTEM

This paper proposes an extension to the regional econometric input–output model (REIM) [Conway, R.S. (1990) The Washington Projection and Simulation Model: A Regional Interindustry Econometric Model. International Regional Science Review, 13, 141–165; Israilevich, P.R., G.J.D. Hewings, M. Sonis and G.R. Schindler (1997) Forecasting Structural Change with a Regional Econometric Input–Output Model. Journal of Regional Science, 37, 565–590]. We integrate a demand system with age and income parameters into the REIM. The extended model thus addresses concerns about the effects of household heterogeneity. The initial testing is conducted with a model for the Chicago metropolitan area. First, using aggregate expenditure data by income and age groups, the almost ideal demand system with group fixed effects is constructed. Next, the estimated demand system is linked to the REIM to reflect long-term changes in the age and income distribution of households. The long-range simulation from the extended model takes into account structural changes in expenditure type stemming from changing demographic composition. The extended model further broadens the scope of impact analysis under various scenarios associated with age and income changes.     

DEVELOPING A MULTI-SCALE MULTI-REGION INPUT–OUTPUT MODEL

Many efforts have recently been devoted to developing global multi-region input–output (GMRIO) models. Unfortunately, the scales of GMRIO models do not allow them to capture the heterogeneity of regions within a single country. Multi-scale models can provide more comprehensive analyses capable of capturing the interdependencies of the global economy while preserving regional differences. The primary objective of this research is to develop methods for integrating multi-region input–output data sets from multiple spatial scales into multi-scale multi-region input–output (MSMRIO) models. These methods result in models that may have unusual features such as non-square trade coefficient matrices and a mix of industry-by-industry and commodity-by-commodity technical coefficients. To demonstrate the feasibility of MSMRIO modelling, a Canada-centric model was developed. This model includes 47 countries and Canada's 13 subnational regions. A MSMRIO model provides a tool to analyse global issues with a more spatially detailed focus.     

AN ENVIRONMENTAL/INPUT–OUTPUT LINEAR PROGRAMMING MODEL TO REACH THE TARGETS FOR GREENHOUSE GAS EMISSIONS SET BY THE KYOTO PROTOCOL

The Kyoto Protocol contains legally binding targets for greenhouse gas (GHG) emissions for industrialized countries. The importance of this agreement and the elaboration of a climate change policy make it necessary to define and establish national policy measures and to bring into force environmental regulations that will reduce GHG emissions. Extending our knowledge of the economic-ecologic relationships that exist within the production sphere can assist in defining and implementing successful environmental policies. In this paper, an Environmental/Input–Output linear programming model is proposed. To develop the model we consider the input–output model as a linear programming problem combining two types of restrictions: environmental restrictions establishing GHG emission targets, and economic restrictions. The model shows how targets for the emissions of GHGs may be reached and can affect production activity composition.