Disaggregating input–output tables in time: the temporal input–output framework

The input–output framework has evolved dramatically since its initial formulation. New analytical techniques and extensions have allowed a more comprehensive assessment of the economy and expanded its applicability. Nonetheless, the core of the framework has remained unchanged: an annually compiled input–output table, which conveys monetary flows between sectors in a region in a particular year. Hence, the technical coefficients derived from it are ‘average’ input compositions, neglecting fluctuations in production capacity, seasonality and temporal shocks within that period. This paper develops a consistent methodology to disaggregate the annual input–output table in its time dimension in order to estimate intra-year input–output matrices with distinct technical structures for a particular year. The main advantages in relation to the annual model are to allow seasonal effects to be studied within the input–output framework, to better understand the process of coefficient change and to offer a more comprehensive dynamic view of production.     

Factors driving embodied carbon in international trade: a multiregional input–output gravity model

ABSTRACT

Concerns about the effects and consequences of climate change have notably increased in recent decades. Despite large advances in the understanding of this phenomenon, further research into the determinants of gas emissions is necessary, to shed light on the responsibilities of producers and consumers, and their potential contribution to mitigation strategies. This paper studies the trajectories and determinants of carbon embodied in world trade during a period of 15 years. Our methodology relies on a multiregional input–output model, environmentally extended. Drawing on data from the World Input–Output Database, we estimate embodied emissions in bilateral flows. Then, we assess the determinants of CO₂ emissions embodied in trade, combining input–output modelling with trade gravity panel data analysis. This paper offers a methodological approach that explains and quantifies the underlying factors of carbon trade, integrating the production and consumption perspectives and considering the geographical, structural and institutional context of countries.     

Bayesian estimation of labor demand by age: theoretical consistency and an application to an input–output model

Extended input–output models require careful estimation of disaggregated consumption by households and comparable sources of labor income by sector. The latter components most often have to be estimated. The primary focus of this paper is to produce labor demand disaggregated by workers’ age. The results are evaluated through considerations of its consistency with a static labor demand model restricted with theoretical requirements. A Bayesian approach is used for more straightforward imposition of regularity conditions. The Bayesian model confirms elastic labor demand for youth workers, which is consistent with what past studies find. Additionally, to explore the effects of changes in age structure on a regional economy, the estimated age-group-specific labor demand model is integrated into a regional input–output model. The integrated model suggests that ceteris paribus ageing population contributes to lowering aggregate economic multipliers due to the rapidly growing number of elderly workers who earn less than younger workers.     

Effects of international trade on domestic employment: an application of a global multiregional input–output supermultiplier model (1995–2011)

The effects on domestic employment of international trade and the globalisation of supply chains are as politically controversial as they are empirically inconclusive. To estimate them we extend the global multiregional input–output framework by endogenising demand for both domestic and imported intermediates, private business investment and household non-durable consumption – or equivalently, we generalise the supermultiplier formula. The model accounts, in particular, for the employment consequences of economic integration and those channelled through integration. We estimate these foreign sector effects alongside those of domestic origin using a recursive hierarchical structural decomposition analysis and statistics from the World Input–Output Database and National Accounts that cover years 1995–2011. Focusing on Spain, Italy, France, Germany, the UK, the US, Japan and China we answer the following questions: To what extent did international linkages deriving from international trade affect domestic employment? Did domestic employment benefit from economic integration?     

An input–output virtual laboratory in practice – survey of uptake,usage and applications of the first operational IELab

ABSTRACT

The Industrial Ecology Virtual Laboratory (IELab) is a collaborative cloud-computing platform for compiling large-scale, high-resolution, enviro-socio-economic accounts based on multi-region input–output tables and for conducting integrated sustainability assessment projects. These include, for example, assessments of biofuels and low-carbon construction materials or high-resolution waste modelling. This contribution provides a structured review of IELab applications that were published in either peer-reviewed journal papers or in the form of conference proceedings. The main research question posed is ‘What are the specific features of IELab that were used in the research and could the research have happened without them?’ It is investigated whether the IELab has actually and truly enabled new research. A detailed analysis of IELab characteristics and their usage is presented. The results can help with the design of new research projects and inform existing and prospective users of the IELab about the options for academic research and practical applications.     

A new sub-national multi-region input–output database for Indonesia

ABSTRACT

As a large archipelago with significant geographical variation and economic diversity, Indonesia requires detailed regional information when subjected to economic modelling. While such information is available, it however has not been integrated and harmonised into a comprehensive input–output database, thus preventing economic, social, and environmental modelling for investigating sub-national regional policy questions. We present the new IndoLab, a collaborative research platform for Indonesia, enabling input–output modelling of economic, social, and environmental issues in a cloud-computing environment. Within the IndoLab researchers are for the first time able to generate a time series of regionally and sectorally detailed and comprehensive, sub-national multi-region input–output (MRIO) tables for Indonesia. By integrating a multitude of economic, social, and environmental data into a single standardised processing pipeline and harmonised data repository, the IndoLab is able to generate MRIO tables capturing up to 1148 sectors, and 495 cities and regencies. Researchers can freely choose from this detail to construct tables with customised classifications that suit their own research questions. First results from the IndoLab clearly demonstrate the unique characteristics of regions in terms of their sectors’ employment intensity. Thus, the IndoLab has great potential for investigating policy questions that cannot be comprehensively addressed using a single national database.     

Appropriate assumption on cross-hauling national input–output table regionalization

Input–output tables are useful for regional economic analyses. Although scholars often regionalize national input–output tables, cost-related issues make surveying regional trade flow difficult; hence, non-survey approaches are implemented instead. While location quotient (LQ) approaches have been used widely, they ignore cross-hauling in interregional trade. Therefore, alternative non-survey approaches with different assumptions on cross-hauling are used, such as cross-hauling depends on regional size and cross-hauling is proportional to its potential determined by output or demand. This study concludes that the most appropriate assumption, as per the relative performance of non-survey approaches, is that cross-hauling is in proportion to trade volume.     

A general weighted least squares approach for the projection of input–output tables

In the context of input–output analysis, it is often necessary to update a matrix for a date when only the sum of its columns and rows are known. This projection problem is quite similar to temporal disaggregation. I borrow from this literature a class of solutions for which the exact result can be implemented without iteration. These solutions minimize the adjustment made to the out-of-date matrix and as such can be said optimal according to a chosen criteria. The framework I expose is flexible enough to encompass many of the existing methods and develop new ones. I propose one of such methods to project a matrix between two given benchmarks. I exemplify the technique on 35 years of input–output tables for France and show in particular that the issue of negative cells can be avoided.     

On the financial balance of input–output constructs: revisiting an axiomatic evaluation

Financial balance is fundamental to input–output (IO) analysis, and consequently the respect of this balance is one of the dominant criteria in evaluating IO constructs. Kop Jansen, and ten Raa [(1990) The Choice of Model in the Construction of Input–Output Coefficients Matrices. International Economic Review 31, 213] proved that the byproduct-technology construct (BTC) and the industry-technology construct (ITC) do not generally conserve financial balance. In contrast, Majeau-Bettez et al. [(2016) When do Allocations and Constructs Respect Material, Energy, Financial, and Production Balances in LCA and EEIO? Journal of Industrial Ecology 20, 67–84] demonstrated that the BTC necessarily respects financial balance and that the ITC is always financially balanced when applied to data recorded in monetary units. The present article resolves this paradox.     

A network approach for assembling and linking input–output models

Input–output (IO) models, describing trade between different sectors and regions, are widely used to study the environmental repercussions of human activities. A frequent challenge in assembling an IO model or linking several such models is the absence of flow data with the same level of detail for all components. Such problems can be addressed using proportional allocation, which is a form of algebraic transformations. In this paper, we propose a novel approach whereby the IO system is viewed as a network, the topology of which is transformed with the addition of virtual nodes so that available empirical flow data can be mapped directly to existing links, with no additional estimation required, and no impact on results. As IO systems become increasingly disaggregated, and coupled to adjacent databases and models, the adaptability of IO frameworks becomes increasingly important. We show that topological transformations also offer large advantages in terms of transparency, modularity and increasingly importantly for global IO models, efficiency. We illustrate the results in the context of trade linking, multi-scale integration and other applications.     

Spatial and sectoral characteristics of China’s international and interregional virtual water flows – based on multi-regional input–output model

This paper provides a systematic analysis of spatial and sectoral characteristics and changes in virtual water flows associated with China’s interregional and international trade based on the China interregional input–output tables of 2002 and 2007. The results show significant improvement in water use efficiency between 2002 and 2007. However, the general spatial patterns and sectoral components of virtual water flows have more or less remained during the period. Almost all Chinese provinces are net exporters of virtual water in international trade. In interregional trade, the dominant direction of virtual water flow is from peripheral provinces to eastern coastal provinces. The agricultural sector plays an important role in shaping this direction and has significant impacts on water uses in exporting provinces, some of which are water scarce. The results of this study clarify some confusions concerning mismatches between regional water endowments and virtual water trade within China and with other countries.     

Properties of inefficiency indexes on ?input, output? space

We analyze efficiency measurement in the full á\langleinput, output?\rangle space. We posit four types of axioms: indication (of efficient production bundles), monotonicity, independence of units of measurement, and continuity (in technologies as well as input and output quantities). Impossibility results establish a tension between indication and continuity. We focus on seven well-known inefficiency indexes from the operations-research and economics literature, establishing the properties they satisfy—and do not satisfy—on a general class of technologies satisfying minimal regularity conditions and on the subset of these technologies satisfying convexity. We also discuss several other indexes that are dominated by or very similar to these seven indexes. The set of properties satisfied by these indexes elucidates the trade-offs faced in selecting among the indexes.     

Improving footprint calculations of small open economies: combining local with multi-regional input–output tables

In a small, open and resource-poor economy, import and export dependency have an ever-growing impact on local policy decisions, which makes local (environmental) policy-makers increasingly depend on global data. This increases the interest in models that link local production and consumption data to global production, trade and environmental data. The recent increase in availability of global environmentally extended multi-regional input-output tables (EE-MRIO tables) provides an opportunity to link them with existing local environmentally extended input-output tables (EE-RIO tables). These combined tables make it possible (1) to analyse the links between local and global production and consumption and (2) to study global value chains, material use and environmental impacts simultaneously. However, estimations using input-output (I–O) analyses contain errors due to imperfect databases. In this article the magnitude of specification, aggregation and time errors are estimated and compared. The results show the need to combine local datasets with multi-regional ones and show that highest detailed (country and sector levels) as well as time series of I–O tables are the way forward for using I–O analyses in local policy-making. The paper provides guidance on trading off investments in model adoption and/or extension and the reliability of estimation results.     

Using input–output models to estimate sectoral effects of carbon tax policy: Applications of the NGFS scenarios

The Network of Central Banks and Supervisors for Greening the Financial System (NGFS) has engaged in scenario analysis that estimates a $200/ton carbon tax would be required to transition to net zero carbon by 2050. Using a $200/ton carbon tax as a base, this paper uses input–output (IO) modeling to generate price and revenue effects of a carbon tax. Results from these models, which can only be interpreted as the short-run, upper-bound effects of the carbon tax policy, imply that in response to a $200/ton tax on CO₂e emissions, carbon-intensive industries, such as agriculture, extraction, transportation, utilities, and chemicals, may experience price increases in the range of 10-30 percent. Other industries will also experience price increases, but to a lesser degree, due to increased input costs associated with the tax. In addition, modeling results also suggest that industries facing elastic pricing regimes may face similar-sized declines in revenues as a consequence of the carbon tax. Rank-ordered impact results from these models can be utilized by bank supervisors and firms to adequately plan for sectoral-level transition risk within their lending and/or investment portfolios.     

Choosing among alternative technologies: conditions for assuring the feasibility of an input–output database or scenario

The conceptual reach of the basic input–output modeling framework is substantially extended by new models that incorporate the economic logic of comparative advantage as the basis for the endogenous choice among alternative production technologies. This paper establishes procedures that define the conditions under which the database used for scenario analysis in this extended framework assures the existence of an economically feasible solution. We provide a criterion for structural feasibility, the property established by the Hawkins–Simon condition for the basic input–output model, and introduce a criterion for scale feasibility. The logic underlying the tests is illustrated by numerical examples based on the Rectangular Choice-of-Technology model and database. These procedures can be particularly useful for incorporating engineering and other technical sources of information into multi-regional input–output databases; they can also provide substantial underlying detail about individual technologies, sectors, and factors of production for both feasible and infeasible scenarios.     

Do we estimate an input or an output distance function? An application of the mixture approach to European railways

In this paper, we estimate parametric input and output distance functions and discuss how to estimate a mixture/latent class model (LCM) involving the output and input distance functions in the context of multi-input and multi-output production technology. The proposed technique is applied to a panel data on European Railways (1971–1994). This model allows us to identify determinants of the efficiency orientation, thereby providing useful information that can help researchers to choose between the input and the output-oriented approaches. In addition, we develop cross-indices that can be used to compute input (output) technical inefficiency from the estimates of output (input) distance function.

Supply chain fragmentation,input–output tables and spillovers from foreign direct investment

The literature on the impact of multinationals on domestic firms' productivity points to supply chain linkages with multinational firms as the main channel for positive spillover effects. Local and multinational firms' relative positions in the supply chain are typically determined through the use of input–output tables. For a panel of Romanian firms, we show that the level of industry aggregation in these tables and the applied spillover definitions bear an important impact on estimated spillover effects. We find that the total impact of foreign presence – irrespective of the channel – is considerably larger when detailed IO-tables are used. When more aggregated tables are used, one is likely to misclassify a considerable number of supplier–client activity as within-industry competitive activity. Including within-industry supply and use in the measures of supplier–client activity results in a further increase of the spillover effect on local suppliers, whereas the within-industry spillover effect disappears.     

Accounting for value added embodied in trade and consumption: an intercomparison of global multiregional input–output databases

Global multiregional input–output (MRIO) tables constitute detailed accounts of the economic activity worldwide. Global trade models based on MRIO tables are being used to calculate important economic and environmental indicators such as value added in trade or the carbon footprint of nations. Such applications are highly relevant in international trade and climate policy negotiations, and consequently MRIO model results are being scrutinized for their accuracy and reproducibility. We investigate the variation in results from three major MRIO databases by comparing underlying economic data and territorial and consumption-based results across databases. Although global value-added accounts were similar across databases, we find some significant differences at the level of individual countries and sectors. Model disagreement was relatively stable from the territorial to the consumption perspective. Pairwise matrix comparison statistics indicated that the Global Trade Analysis Project and World Input-Output Database MRIO tables were overall more similar to each other than either was to the Eora database.     

New multi-regional input–output databases for Australia – enabling timely and flexible regional analysis

ABSTRACT

Decision-making at regional scales requires timely information. Within four months of the release of official national statistics, we have produced a time-series (2008–2015) of balanced sub-national, multi-regional supply-and-use tables (MR-SUT), integrated with a set of socio-economic and environmental accounts. This was achieved using the Australian IELab, where data used in this study are available (https://ielab.info/resources/91). Four multi-regional, environmentally extended supply-use tables regionalised in different ways were produced to demonstrate the flexibility of tailoring input–output models to specific research or policy questions. Results for satellite coefficients are sensitive to the chosen regional grouping and method for regionalisation. We demonstrate the relevance of such purpose-built information to government and corporate decision-makers by analysing the indirect economic and employment consequences of a slowdown of the mining boom in Western Australia. The demonstrated innovations in flexibility and timeliness will help move past some of the limitations that have historically hindered the uptake and utility of applied input–output analysis.     

An applied stochastic model of the quality–quantity trade-off in the public health care sector

It is a striking feature of the many of the developing country public service sectors that the sectors in question often overproduce the quantity of services but underproduce the quality. This feature, which is exemplified in this paper, is rooted in a wide spectrum of economic and sociological factors ranging from the economic and sociological profile of the service receiving people to the asymmetric density of service-receiving population across their regions. This feature, we conjecture, is a source of a considerable degree of suboptimality in some of the developing countries. If our conjecture is correct, correcting such suboptimalities is likely to yield significant welfare improvements that could help speed up the process of development in the underdeveloped regions of the world. To analyze the supoopimalites in question, we will first develop a concept (and a model) of optimal quality in the public service sector, which indicates the level of quality that maximizes expected public satisfaction subject to available resources. Resources are used in an efficient manner to produce the service in question. The concept and the model in the paper make a needed contribution to the quality discourse by presenting a way of determining the quality improvements (or adjustments) necessary to achieve optimum in the public service sector. The paper presents an application (a case study) of this new concept in the public healthcare sector in Turkey, and explores the differences between the actual and optimal quality in the sector in question. It turns out that there is a considerable difference between the actual and optimal levels of quality (as well as those of quantity) in the Turkish public healthcare sector in an overpopulated city (Istanbul), indicating a significant overproduction of quantity and underproduction of quality. Thus, to achieve the optimal levels, the sector should increase quality and reduce quantity by a considerable margin. The quantified differences (gaps) between actual and optimal levels point out a considerable room for welfare improvement. Optimum-seeking adjustments closing these gaps could be shown to lead to considerable satisfaction and welfare gains, the measurement of which is worthy of future research.