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In this paper, we develop a metric of reshoring at the macroeconomic level, at the level of industries or countries. Our dynamic measure computes the change in the domestic–foreign input ratio and therewith captures the idea of moving production back to the home country. Additional conditions ensure that the measure is confined to actual reshoring and does not pick up, for example, mere changes in the scale and composition of production. We show that reshoring is only weakly approximated by reduced offshoring. We compute the reshoring intensity from the World Input Output Database and illustrate the use of the data with several applications. Specifically, we compute trends in reshoring for examples of countries and industry sectors, we investigate reshoring from China, and examine the impact of an increasing degree of automation for reshoring in emerging and developing economies.

The construction sector has a special interest in the case of the Spanish economy, given its large economic dimension and environmental impact, particularly during the real estate boom prior to the last economic crisis that started in 2008. We study the CO2 emissions of construction activities in 2007, at the height of the construction boom, in the context of the productive structure of Spain. For this, we use an input–output subsystem method, which allows us to study the productive structure of the subsystem’s activities, taking into account its links with the rest of the sectors. The decomposition of total emissions in four explanatory components allows us to make a classification of the different sectors according to the type of relationships that are established between the subsystem and the rest of the economy. We derive some implications for environmental policy from the analysis of these interrelations.

This paper discusses a new approach to quantify trade creation and trade diversion that relies on the structural decomposition analysis in an inter‐country input–output framework. The proposed measure captures the contribution of trade creation (diversion) between two countries to the GDP growth of the home country, partner country and third countries. For a trial calculation, the author uses the 2016 release of the OECD inter‐country input–output tables and focuses on the period 2000–11. Creation, diversion, but also contraction of trade flows are shown to be intrinsic to any pair of countries that may or may not be linked by a trade agreement. There is no evidence that the rise of free trade agreements in 2000s is associated with higher magnitude of these trade effects for an average country pair. The proposed approach is thought to be a useful alternative to econometric estimates of trade creation and trade diversion available to date.

Global environmental and resource problems ask for new ways of managing the production and consumption of resources. The implementation of new paradigms, such as the circular economy, requires decision-makers at multiple levels to make complex decisions. For this, clear analyses and modeling of scenarios are of utmost importance. Meanwhile, as the sophistication of databases and models increases so does the need for user-friendly tools to use them. The RaMa-Scene web platform reduces these barriers by allowing users to visualize easily diverse impacts of implementing circular-economy interventions. This online web platform makes use of the multi-regional environmentally extended input-output database EXIOBASE version 3 in monetary units, which has been modified to show explicit transactions of raw materials from recycling activities.

The input/output stability of an interconnected system composed of an ordinary differential equation and a damped string equation is studied. Issued from the literature on time-delay systems, an exact stability result is firstly derived using pole locations. Then, based on the Small-Gain theorem and on the Quadratic Separation framework, some robust stability criteria are provided. The latter follows from a projection of the infinite dimensional state on an orthogonal basis of Legendre polynomials. Numerical examples comparing these results with the ones in the literature are proposed and a comparison of its efficiency is made.

The European Union (EU) set ambitious goals toward more sustainable use of plastics, but the basis for measuring performance and monitoring progress toward these goals remains inadequate due to a limited understanding of the complex systems behind plastic consumption. In this work, we study the region-wide material flows of plastics related to packaging in 2014 using a hybrid approach that combines data on the production and end-of-life management of plastic packaging with a monetary input-output model for the EU. The approach enables us to gain insight into interindustry flows and the connection between production and final demand. We map supply chains with a relatively high resolution, including polymer types, packaging forms and application categories. Results estimate the total packaging placed on the market (POM) and then discarded amounted to 18,000 kt., excluding a net increase in stocks of 500 kt. This means that waste generation could have been up to 15% higher than accounted in official statistics, reinforcing potential underreporting accounts as well as remaining data gaps. Thirty-five percent of postconsumer packaging waste was directed toward recycling. However, only 5% contributed to new domestic packaging production, a reflection of the broad challenges to plastic circularity. Although first steps are taken in this work, we point to an acute lack of information on industrial streams, compounded by missing policy focus, for example, on transport packaging. We suggest areas for deeper investigation and emphasize the potential of hybrid approaches to establishing baselines and assessment of both production and consumption-side mitigation strategies.

We present a multidimensional generalization of the GRAS method (nD-GRAS) for the estimation of multiple matrices in an integrated framework. The potential applications of this method in regional and multi-regional input–output analyses based on national/regional accounts frameworks are many. We provide two real applications, a 3D-GRAS that estimates a use table at basic prices jointly with valuation matrices for Denmark; and a 4D-GRAS for estimating intercountry input–output tables with OECD data. We show that higher dimensional GRAS methods provide more consistent and accurate estimates than those with lower number of dimensions. We provide the analytical closed-form solution and the RAS-like algorithm for an easy operationalization.

Summary Global multiregion input-output (MRIO) tables have been developed to capture international spillover effects due to demand in one country and production in other countries. International spillovers have been growing and have become so dominant, especially in environmental analysis, that their inclusion is essential when analyzing impacts of consumption. MRIO tables give full coverage of the world economy, but do not always respect the official data of a given country. When international spillovers also cause increased production in the country of demand, we see what are known as “feedback effects.” As coupled models are being developed that make use of an official foreground national input-output table (IOT) alongside an existing global MRIO, we are left in the situation where a coupled model does not use the official foreground information when modeling international feedback loops. The question thus arises: How large are these feedback loops for different environmental impacts? We look specifically at the amount of domestic production that is embodied in imports back into that region. We find that for emissions, the feedbacks are small, usually

This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal set, which are solved offline, for the underlying online MPC optimization problem. The main attractive feature of the proposed scheme in comparison with previously published results is that all offline computations are now based on the convex optimization problem, which significantly reduces conservatism and computational complexity. Moreover, the proposed scheme can handle a wider class of linear parameter-varying input-output models than those considered by previous schemes without increasing the complexity. For an illustration, the predictive control of a continuously stirred tank reactor is provided with the proposed method.

The Input-Output model has made extensive use of graph and network theory, methods and conclusions, in order to carry out structural analysis; such extensions have yielded powerful insights on the relationships existing between industries in an economic system. It is customary in the field to take a deterministic perspective when analysing economic structures, using various measures derived from the Input-Output tables; yet the model can include stochastic experiments. This paper takes that course of action, aiming at modelling the Greek economic structure from a qualitative viewpoint for 2005 and 2010; moreover, sectors are divided by groups of differentiated technology intensity. The methodology is based on a model based on families of distributions that allow predicting and analysing network structures. Results are reached by a probabilistic approach, producing interesting insights about the economic structures under study, while revealing different behaviour of the different groups of industries, classified by technological intensity.

This study is a contribution to the ongoing debate on the performance of various non-survey techniques for constructing sub-territorial input-output tables. Three aspects of the behaviour of the methods are analysed: performances in reproducing ‘true’ input coefficients, variability of error, and direction of bias. The analysis uses real data and in particular the world input-output table. The most important aspect that emerges from the analysis is that even though simple location quotient (SLQ) has been identified as one of the most robust methods, its performance drops when confronted with Input Output Tables characterized by a high percentage of technical coefficients close to zero. Also the cross industry location quotient (CILQ), the semi logarithmic location quotient (RLQ), the symmetric cross industry location quotient (SCILQ) methods behave in a similar way. On the contrary, the performance of the methods the Flegg location quotient (FLQ) for δ = 0.2 and the Augmented Flegg location quotient (AFLQ) for 0.2 ≤ δ ≤ 0.3 are not affected by this situation.

Graph theory is a fundamental tool in the study of economic issues, and input–output tables are one of the main examples. We use the interpretation of the labour market through networks to obtain a better understanding on its overall functioning. One benefit of the network perspective is that a large body of mathematics exists to help analyze many forms of networks models. If an economic system has obtained a suitable model, then it becomes possible to utilize relevant mathematical tools, such as graph theory, to better understand the way the labour market works. This interpretation allows us to employ the concepts of coverage, invariance, orbit and the structural functions supply–demand and competition and interpret them from the point of view of circular flow. In this paper, we aim to interpret the labour market through networks that are represented by graphs and where characteristic concepts of chaos theory such as cover, invariance and orbits interact with the concept circular flow. Finally, an example of this approach to labour markets is described, and some conclusions are drawn. Copyright © 2016 John Wiley & Sons, Ltd.

Summary Environmentally extended input-output (EEIO) databases are increasingly used to examine environmental footprints of economic activities. Studies focusing on China have independently, repeatedly developed EEIO databases for China. These databases are usually not publicly available, leading to repeated efforts, inconsistent with one another using different approaches, of limited environmental accounts, and lacking transparency, preventing continuous updating. We developed a transparent, comprehensive, and consistent Chinese EEIO database covering a wide period of time (currently 1992, 1997, 2002, and 2007 for which benchmark input-output tables [IOTs] are available), sector classifications (original sector classifications in benchmark IOTs, a 45-sector classification commonly used in China's environmental and energy statistics, and a 91-sector classification with maximized sector resolution ensuring temporal consistence), and environmental satellite accounts for 256 types of resources and 30 types of pollutants in this study. Moreover, the environmental satellite accounts cover households in addition to sectors, allowing developing closed models. We make this database publicly available with open access for broader dissemination (www.ceeio.com). We demonstrate the database by evaluating environmental pressures of Chinese products in 2007. Comparisons of our database with previous studies validate its rationality and reliability.

This study investigates relations between second language (L2) lexical input and output in terms of word information properties (i.e., lexical salience; Ellis, 2006a). The data for this study come from a longitudinal corpus of naturalistic spoken data between L2 learners and first language (L1) interlocutors collected over a year's time. The corpus was analyzed using word information properties related to concreteness, familiarity, and meaningfulness to examine word repetitions between input and output, correlations between the input and the output, linear trends over time, and whether lexical properties in the output were predictive of growth in TOEFL scores. The results indicate that L2 learners are more likely to repeat word types found in L1 input and that L1 interlocutors and L2 learners follow similar linear trends over time such that words with lower concreteness, lower familiarity, and lower meaningfulness were produced over the course of the study in both the input and output. A linear mixed model analysis showed that decreases in concreteness scores explained significant gains in TOEFL scores over time. The findings from the study indicate strong associations between L2 input and output and provide evidence linking development in word information properties to development in academic English proficiency. [ABSTRACT FROM AUTHOR]

Summary The technique of linear matrix inequalities is a powerful method for solving optimization problems. In this paper, a sliding function vector was calculated using linear matrix inequalities approach. This technique provided optimal values of the coefficients of the sliding function vector, which led to the reduction of the reachability phase. Then, a discrete second-order sliding mode control for multivariable systems was developed using this optimal sliding function vector. Two examples were used in order to illustrate the effectiveness of the proposed strategy. Simulation results prove good performances in terms of reduction of the reachability phase. Copyright © 2016 John Wiley & Sons, Ltd.

As an increasingly adopted renewable energy resource, solar power has a high potential for carbon emission reduction and economic development. This paper calculates the impact on job, income and output creation of a new solar power plant in an input-output framework. The contribution is twofold. First, we compare the multipliers generated by the construction and operation/maintenance of a plant located in California with those it would have generated had it been built in Arizona. Second, we point out the differences in the results obtained with the popular IMPLAN software from those we get with the solar photovoltaic model of JEDI.

Summary This paper is concentrated on the problem of fault estimation for a class of linear systems with partially dynamic uncertainty and actuator faults. A novel input–output-based fault estimation approach is proposed, by which the estimates can asymptotically converge to the magnitudes of the actuator faults, and the asymptotic convergence of the estimation is theoretically proved. Some important properties related to the corresponding fault errors are obtained. The proposed input–output-based fault estimation method can exponentially weaken the effects of the fault derivatives on the fault error dynamics. Based on the online estimates, a corresponding robust fault-tolerant control policy is designed, so that the closed-loop system is asymptotically stable and the control output curves can asymptotically trace to the normal control output curves. Finally, three examples are given to show the effectiveness, merits, and applications of the proposed methods. Copyright © 2016 John Wiley & Sons, Ltd.

Performance isolation has long been a challenging problem for disk resource allocation in virtualized environments. While there have been many researches working on I/O performance isolation and disk utilization, none of them addresses the I/O performance isolation and disk utilization as a whole. To this end, we investigate the impact of current disk I/O performance isolation schemes on disk I/O utilization. Interestingly, our studies report that current isolation schemes bring unnecessary disk idle and reduce the overall disk I/O performance because of ignoring the disk states and characteristics of requests. Accordingly, we propose an adaptive proportional-share I/O scheduling framework, named iShare, in virtualized environments. iShare not only ensures I/O performance isolation through proportionally allocating time slices according to the weights of virtual machines but also preserves high disk efficiency by detecting disk states and adaptively adjusting the time slice size based on characteristics of requests. We implement a prototype of iShare on the Xen platform. The experimental results show that iShare ensures I/O performance isolation while improving disk I/O efficiency, compared with Blkio i.e., the default I/O performance isolation method in Xen, iShare increases disk I/O bandwidth by 58% and slightly improves the I/O performance isolation for the sequential write applications. Copyright © 2015 John Wiley & Sons, Ltd.

This paper introduces HybridMR, a novel model for the execution of MapReduce (MR) computation on hybrid computing environment. Using this model, high performance cloud resources and heterogeneous desktop personal computers (PCs) in Internet or Intranet can be integrated to form a hybrid computing environment. Thanks to HybridMR, the computation and storage capability of large scale desktop PCs can be fully utilized to process large scale datasets. HybridMR relies on two innovative solutions to enable such large scale data-intensive computation. The first one is HybridDFS, which is a hybrid distributed file system. HybridDFS features reliable distributed storage that alleviates the volatility of desktop PCs, thanks to fault tolerance and file replication mechanism. The second innovation is a new node priority-based fair scheduling (NPBFS) algorithm has been developed in HybridMR to achieve both data storage balance and job assignment balance by assigning each node a priority through quantifying CPU speed, memory size, and input and output capacity. In this paper, we describe the HybridMR, HybridDFS, and NPBFS. We report on performance evaluation results, which show that the proposed HybridMR not only achieves reliable MR computation, reduces task response time, and improves the performance of MR, but also reduces the computation cost and achieves a greener computing mode.

This article provides guidance to prudent use of the World Input–Output Database (WIOD) in analyses of international trade. The WIOD contains annual time-series of world input–output tables and factor requirements covering the period from 1995 to 2011. Underlying concepts, construction methods and data sources are introduced, pointing out particular strengths and weaknesses. We illustrate its usefulness by analyzing the geographical and factorial distribution of value added in global automotive production and show increasing fragmentation, both within and across regions. Possible improvements and extensions to the data are discussed.

An innovative technique to build stochastic frequency-domain macromodels of generic linear multiport systems is presented. The proposed method calculates a macromodel of the system transfer function including its statistical properties, making it tailored for variability analysis. The combination of the modeling power of the Vector Fitting algorithm with the Polynomial Chaos expansion applied at an input-output level allows to accurately and efficiently describe the system variability features. Thanks to its versatility and automated order selection, the proposed technique is suitable to be applied to a large range of complex modern electrical systems e.g., filters and interconnections and can tackle the case of correlated random variables. The performance in terms of accuracy and computational efficiency of the proposed method is compared with respect to the standard Monte Carlo analysis for two pertinent numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.

Summary Transformations for high-performance superscalar, vector, and parallel processors maximize parallelism and memory locality. Often parallelizing compilers apply transformations, such as loop parallelization and loop vectorization, to convert a sequential array-handling program into a parallel program. Validation of such transformations is extremely useful in the prevalent high-performance computing environment. This paper proposes a novel algorithm for construction of the dependence graph of the generated parallel programs. These transformations are validated by checking equivalence of the dependence graphs of the original sequential program and the transformed parallel program using a standard algorithm reported in the literature. The above equivalence checker works even when the above parallelizing transformations are preceded by various enabling transformations except for loop collapsing transformation that changes the dimensions of the arrays. In the present paper, the scope of the equivalence checker has been expanded to handle this special case by informing it of the correspondence between the index spaces of the corresponding of input and output arrays in the sequential and the parallel programs. The proposed methods are implemented and tested against a set of available benchmark programs that are parallelized by the polyhedral auto-parallelizer LooPo and the auto-vectorizer Scout.

Author(s): Tolic, D; Sanfelice, RG; Fierro, R | Abstract: This paper investigates stability of nonlinear control systems under intermittent information. Following recent results in the literature, we replace the traditional periodic paradigm, where the up-to-date information is transmitted and control laws are executed in a periodic fashion, with the event-triggered paradigm. Building on the small gain theorem, we develop input-output triggered control algorithms yielding stable closed-loop systems. In other words, based on the currently available (but outdated) measurements of the outputs and external inputs of a plant, a mechanism triggering when to obtain new measurements and update the control inputs is provided. Depending on the noise in the environment, the developed algorithm yields stable, asymptotically stable, and Lp-stable (with bias) closed-loop systems. Control loops are modeled as interconnections of hybrid systems for which novel results on Lp-stability are presented. The prediction of a triggering event is achieved by employing Lp-gains over a finite horizon. By resorting to convex programming, a method to compute Lp-gains over a finite horizon is devised. Finally, our approach is successfully applied to a trajectory tracking problem for unicycles. © 2014 John Wiley a Sons, Ltd.

This article empirically evaluates the results from input-output (I-O) life cycle assessment (LCA) models of the United States for 2002, based on different sources of data: demand-side survey data; supply-side data with homogeneous prices; and supply-side data with heterogeneous prices. These I-O-based results are also compared with those from process LCA databases. The underlying approach is based on the theoretical insight previously developed. The results show significant differences and offer useful heuristic insight: The survey-based data set seems better for sectors that use a large amount of resources and have large intrasectoral transactions. But, it exhibits many missing values. Homogeneous price-based calculation with supply-side data is easiest because of minimal data needs and simplifying assumption on prices. The result shows relatively complete coverage and obeys mass and energy balances. The heterogeneous price-based data set overcomes the price homogeneity assumption, but the result is sensitive to price accuracy. Overall, it is not possible to declare any currently available data sets to be the best, although survey- and heterogeneous price-based data sets may be improved with more information. This insight is based on comparing direct consumption of fossil resources. Comparison of cumulative consumption reduces the disparities among data sets from error cancellation. Further comparison of process- and I-O-based inventories shows that the former values are often larger than the latter, with the two supply-side data sets being closer to process-based data. These results should be useful for choosing between available data to build the best possible I-O and hybrid LCA models and for further research on enhancing their quality.

Summary The reverse mode of automatic differentiation executes the adjoint statements induced by each statement in the original program in the reverse order of the original program flow. This program flow reversal commonly requires storage of information on the control flow of the original program. In addition, intermediate values of variables that are overwritten have to be recorded, as these values may later be needed to compute the partial derivatives of the corresponding statement. The stored information will be accessed in reverse order of being written. This runs contrary to many assumptions made in standard implementations of file systems, operating systems, and input/output (I/O) libraries. A common buffering strategy aimed at speeding up future read requests is to employ read-ahead. This strategy is useful for accesses in forward direction but is considered to be harmful to the performance of the reverse mode. To increase the performance of the reverse mode, it is also advantageous to interleave computations with the data storage and retrieval operations, which can be achieved using multithreading. To this end, we design and implement a novel software called reverse-mode I/O stream (RIOS) that is adapted to these particular requirements of the reverse mode. We show the advantages of RIOS in two empirical case studies, an artificially constructed example of a typical I/O pattern in the reverse mode and a real-world example arising from fluid mechanics, which is studied in Fortran90 and in Matlab where the reverse mode is generated via the automatic differentiation tools Tapenade and ADiMat, respectively. Copyright © 2014 John Wiley & Sons, Ltd.