Development of environmentally extended social accounting matrices for policy analysis in Alberta

This paper outlines the development of inputs to an integrated land use and transportation model based on a series of environmentally extended social accounting matrices (SAMs) for the Canadian province of Alberta. A novel form of industry disaggregation is employed, based on aggregate iterative proportion and a unique formulation of location quotients. Social accounts are extended via the inclusion of detailed household consumption broken down by income quintiles. The SAMs are developed from supply-use matrices. Physical flow accounts are framed as derived demands, acting as necessary inputs to the production of downstream goods and services. Applications to regional economic modeling are considered, as planning authorities increasingly seek to model the environmental impacts of policy. The SAMs are then applied to the assessment of two technology change scenarios: a shift in the provincial electricity generation mix and a transition to a fully electric private automobile fleet.     

THE POWER OF VISIBLE HANDS: AN ENVIRONMENTAL STRUCTURAL DECOMPOSITION ANALYSIS CONSIDERING THE PEOPLE'S DAILY EFFECT

As an organ of the Central Committee of the Communist Party of China, the People's Daily (PD) has a critical influence on China's policies and economy. This study examines the impact of the PD on China's economic structural changes and industry environmental performance. To separate the ‘PD effect’ from other effects in total sectoral CO₂ emission changes, we propose a new variation of structural decomposition analysis using the frequencies of keywords employed in the PD. We use data from the PD for 2001 to 2011 and the Chinese input–output tables for 2002, 2005, 2007, and 2010. The results show that, on average, the PD effect explains about 11% of changes in total sectoral CO₂ emissions. Specifically, the PD has a relatively strong impact on the mining and utility sectors, while its impact on the manufacturing sectors is relatively weak.     

CARBON EMISSION ACCOUNTING IN MRIO MODELS: THE TERRITORY VS. THE RESIDENCE PRINCIPLE

Consumption-based CO₂ emissions, which are commonly calculated by means of environmentally extended input–output analysis, are gaining wider recognition as a way to complement territorial emission inventories. Although their use has increased significantly in the last years, insufficient attention has been paid to the methodological soundness of the underlying environmental extension. This should follow the internationally agreed accounting rules of the System of Environmental-Economic Accounting, which addresses the activities undertaken by the residents of a country, independent from where these take place. Nonetheless, some footprint calculations use extensions that account for all the activities within the territory, which leads to methodological inconsistencies. Thus, this article introduces the most relevant conceptual differences between these accounting frameworks and shows the magnitude of the gap between them building on the data generated for the EXIOBASE model. It concludes that the differences are high for many countries and their magnitude is increasing over time.     

IMPACT OF URBAN AND RURAL HOUSEHOLD CONSUMPTION ON CARBON EMISSIONS IN CHINA

In this paper, we utilize input–output analysis and decomposition techniques to examine the direct and indirect urban and rural per-capita carbon emissions generated by household consumption in China from 1987 to 2007. The results show that indirect emissions are considerably larger than direct emissions due to households in urban and rural areas. Indirect urban emissions increase significantly because of growing expenditures, but indirect rural emissions do not register the same increase. Direct urban emissions decrease significantly because of changes in the energy mix, but direct rural emissions show only a slight decrease. The increase in the disparity of indirect urban–rural emissions and the decrease in the disparity in direct urban–rural emissions are evident. These findings imply that both energy-saving behavior in the production sector and residential lifestyle transition – particularly in the urban areas – are significant in mitigating carbon emissions in China.     

A SYMMETRIC INPUT–OUTPUT TABLE FOR EU27: LATEST PROGRESS

The European Commission is currently establishing an Environmentally Extended Input–Output (EE-IO) Database for the EU27 developed by the Joint Research Centre at the Institute for Prospective Technological Studies (IPTS). This project attempts to generate an analytical dataset comprising all EU countries and yearly time series for the period 1995–2005. Since, for the time being, IO and environmental accounts data are only available with significant gaps part of the dataset will require estimates based on best available proxy data and reasonable assumptions. This paper is focused on the IO database shaped around Eurostat supply and use tables and symmetric IO tables consistent with the NACE classification. The paper describes the procedure by which the latest preliminary results have been obtained for an aggregate EU27 symmetric input–output table for the year 2000.     

SUPPLY-USE FRAMEWORK FOR INTERNATIONAL ENVIRONMENTAL POLICY ANALYSIS

The technical variation between countries in the production of goods and services, in terms of not only input coefficients, but also emission coefficients, creates scope for international trade to reduce environmental pressures. For this purpose we extend the theory of trade and the environment as to accommodate technical variation between countries in production and emissions. We use and steer close to the extended input and output tables, which include emission data. By treating environmental standards analogous to capital and labor capacity constraints, the aggregation problem for economic and environmental measures gets the same format as the well-understood aggregation problem for labor and capital. In a pilot application we determine the gains to free trade in products and emission permits.     

ADDING SUPPLY-DRIVEN CONSUMPTION MAKES THE GHOSH MODEL EVEN MORE IMPLAUSIBLE

Guerra and Sancho (2011) Guerra, A.-I. and Sancho, F. 2011. Revisiting the Original Ghosh Model: Can It Be Made More Plausible?. Economic Systems Research, 23: 319–328. [Taylor & Francis Online], [Web of Science ®] [Google Scholar] argue that adding a supply-driven consumption function to the Ghosh model diminishes its implausibility in the case of centrally planned economies. Extending the Leontief model with a demand-driven consumption function does make that model more realistic. Extending the Ghosh model, however, makes it even more implausible in the case of a market economy, while it becomes even more problematic as a guide for a centrally planned economy. The prime reason is that complementarities between inputs are negated, not only for firms, but now also for households. Consequently, industry and aggregate output may now increase, while corresponding value added decreases, and vice versa.     

THE ECONOMIC IMPACTS OF VOLUNTARY ENVIRONMENTAL PERFORMANCE OF FIRMS: A CRITICAL REVIEW

Abstract.  New trends in studies on the governance of natural assets include substantial consideration of the role of voluntary initiatives. A traditional economic view states that there is a trade-off between being green and being competitive. According to that view, no voluntary environmental action is expected to occur. To undertake an in-depth analysis of the scope for voluntary action, this paper reviews empirical literature that analyzes the relationship between manufacturing firms' environmental initiatives or performance and economic results. This review moves beyond the general test of the 'pay to be green' hypothesis, preferring instead to systematize empirical results in more specific research questions. Empirical findings of the reviewed literature generally support that there is no penalty for being green. In addition, the typology of firms, the methods utilized for implementing environmental initiatives, the intensity of abatement efforts and stockholders' valuation of green firms have all been shown to have a sizeable influence on the actual economic results of environmental action or management. Consequently, the findings of this paper challenge the traditional strategic theory that predicts widespread free-riding; it holds major implications for environmental policy-making and environmental business decisions.     

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.     

USING TIME-SERIES TO MEASURE UNCERTAINTY IN ENVIRONMENTAL INPUT–OUTPUT ANALYSIS

Environmental Input-Output Analysis (EIOA) is a tool for environmental analysis of broad classes of sectoral activities, taking into account indirect effects in other sectors in the supply chain. The core of EIOA is an input–output table (IOT) and national accounting matrix including environmental accounts (NAMEA) for a fixed base-year. We evaluate the uncertainty in EIOA using a time series of current-price IOT and NAMEA for 13 years from 1990 to 2002. We find annual variations in the current-price IOT and NAMEA, which may represent either realistic changes in production or measurement error. We assume the changes are errors and apply a regression analysis to remove the trends from the underlying data and estimate the uncertainty in the raw IOT. We then calculate the emissions for various final users and sectors to estimate the uncertainties from typical EIOA investigations. Using Monte Carlo analysis, we then investigate how well the variations in the current-price IOT and NAMEA over time may represent uncertainties. The results of this work have several implications for both statistical offices and the analyst. Statistical offices can provide details on data sources, methodologies, and estimates of annual variations. Analysts can incorporate this uncertainty information to understand the implications of uncertainty on their calculations and ultimately the policy recommendations derived from their studies.     

ESTIMATING THE ECONOMIC CONSEQUENCES OF A PORT SHUTDOWN: THE SPECIAL ROLE OF RESILIENCE

This paper develops a methodology for the estimation of the total economic consequences of a seaport disruption, factoring in the major types of resilience. The foundation of the methodology is a combination of demand-driven and supply-driven input–output analyses. Resilience is included through a series of ad hoc adjustments based on various formal models and expert judgment. Moreover, we have designed the methodology in a manner that overcomes the major shortcomings of the supply-driven approach. We apply the methodology to a 90-day disruption at the twin seaports of Beaumont and Port Arthur, Texas, which is a major port area that includes a petrochemical manufacturing complex. We find that regional gross output could decline by as much as $13 billion at the port region level, but that resilience can reduce these impacts by nearly 70%.     

THE BIAS OF THE MULTIPLIER MATRIX WHEN SUPPLY AND USE TABLES ARE STOCHASTIC

The literature on stochastic input–output (I–O) analysis has paid considerable attention to the bias in the Leontief inverse. This paper extends previous studies by assuming supply and use tables (SUTs rather than I–O tables or input coefficients matrices) to be stochastic. This is a natural starting point because SUTs have become the basic data sources for I–O applications. In a Monte Carlo simulation experiment, a given SUT is randomized in two different ways and the effects are determined for eight different multiplier matrices. The analysis is carried out for Spain, Italy, the Netherlands, Germany and Finland, using their SUTs for 2006. The findings indicate that, in general, biases are statistically significant but negligibly small. This corroborates earlier findings obtained for stochastic I–O tables.     

UNDERSTANDING ENVIRONMENTAL RESPONSIBILITY OF CITIES AND EMISSIONS EMBODIED IN TRADE

The attribution of greenhouse gas (GHG) emissions embedded in interregionally traded products to either production or consumption regions is a key issue to the understanding of the global environmental responsibility of metropolitan areas. In this paper we identify GHG emissions for which metropolitan areas assume responsibility by allocating emissions embodied in import and export products to regions of either consumption or production in the cases of three US metropolitan areas. The case studies show that embodied emissions in both export and import products accounted for 63–73% of total GHG emissions directly and indirectly pertaining to these metropolitan economies. These findings suggest that an accounting method that incorporates emissions embodied in product trade has relevance to the development of local policies that govern actions ranging from redirecting metropolitan development patterns toward low carbon emissions to promoting sustainable consumption behavior, particularly those involving the collaboration of cities.     

Closing the Canadian Input–Output Model: Homogeneous vs Non-homogeneous Household Sector Specifications

This paper addresses, on both theoretical and empirical fronts, the task of endogenizing the household sector in a rectangular input–output (IO) model. The formulation of Miyazawa (1976) for square models is extended to the development of an impact matrix for rectangular models. This allows for the numerous household revenue sources to be built into the model. A closed model with non-homogeneous households is developed where individuals are modelled individually and by industry. The perform ance of the non-homogeneous household sector model is compared with a model that has a homogeneous household sector. The model with the non-homogeneous household sector is more sensitive to changes in wages and salaries than to changes in final demand.     

Return of the inoperability

There has been unrest in the research community investigating the inoperability of an economic system under disaster situations. The inoperability input–output model (IIM), which is very popular in the risk management field, has become a center of argument, particularly from the input–output researchers, that IIM is a straightforward application of the standard Leontief input–output model. This paper revisits the concept of inoperability, rather than IIM, and proposes its new role in disaster impact analysis using a conventional tool, i.e. the RAS method, for illustrating how the inoperability of an economic system in the aftermath of disaster can be evaluated. The proposed framework is employed to examine the inoperability of industries resulting from the 1995 Kobe earthquake. The findings of the analysis reveal the usefulness of inoperability concept that can even incorporate resilience (gained operability) using the proposed framework of this paper.     

Extending the input–output model with assets

In this paper, the input–output model is extended with assets. It allows us to examine the various assets that are held and used in production. The requirements of assets that must be held by each sector can thus be specified. Extending the input–output model with assets provides a better alternative to the capital stock matrix in the standard Systems of National Accounts. The input–output model is extended by taking the depreciation of fixed assets into full account. This extension allows for the calculation of total holding coefficients that express the amount of assets that are required to be held in each sector in order to satisfy a unit of final demand. In addition, a dynamic version of the extended model is presented. The extended input–output model has been widely applied in China for various purposes.     

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.     

Alternative Approaches of Physical Input–Output Analysis to Estimate Primary Material Inputs of Production and Consumption Activities

In the last few years, a number of studies have been presented that link material flow accounting and input–output analysis (based on monetary input–output tables) for the calculation of direct and indirect resource inputs for production and consumption activities. The compilation of the first physical input–output tables for some European countries in the 1990s opened new possibilities for linking physical accounting and input– output analysis. Physical input–output analysis has so far only been applied for selected materials, but it has not been used for comprehensive assessments of material requirements of economic activities. In this paper, possibilities and limits of this new input–output approach are clarified. We present and discuss a procedure similar to monetary input– output analysis and develop an alternative approach to account for primary inputs and waste otherwise not included in the analysis. Based on aggregated input–output tables for Germany, we present numerical examples intended to compare the alternative approaches of physical input–output analysis.     

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.     

Does It Make Sense to Apply the Static Open Input–Output Model for Imputation and Structural Decomposition?

This paper aims to stimulate discussion on the question concerning whether input–output (10) analysts should go on applying the static open 10 model in times when data supply and computer capacity allow us to switch to semi-closed 10 models, which are rated as comparative improvements. It is argued that the most frequent of the open 10 model's applications, i.e. imputations and structural decompositions, with a switch to a semi-closed model, lose the properties which make them so attractive: imputations no longer are straightforward assignments of production and primary inputs to the components of total final demand; structural decomposition no longer is an additive assignment of changes of production and primary inputs to sources of structural change. In the author's opinion, imputations and structural decompositions on the basis of the open 10 model should be abandoned.