Spatial spillover effects in determining China's regional CO2 emission growth : 2007-2010

This paper proposes an alternative input-output based spatial-structural decomposition analysis to elucidate the role of domestic-regional heterogeneity and interregional spillover effects in determining China's regional CO2 emission growth. Our empirical results based on the 2007 and 2010 Chinese interregional input-output tables show that the changes in most regions' final demand scale, final expenditure structure and export scale give positive spatial spillover effects on other regions' CO2 emission growth, the changes in most regions' consumption and export preference help the reduction of other regions' CO2 emissions, the changes in production technology, and investment preference may give positive or negative impacts on other region's CO2 emission growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emission growth. All these facts can significantly help better and deeper understanding on the driving forces of China's regional CO2 emission growth, thus can enrich the policy implication concerning a narrow definition of "carbon leakage" through domestic-interregional trade, and relevant political consensus about the responsibility sharing between developed and developing regions inside China.

How does firm heterogeneity information impact the estimation of embodied carbon emissions in Chinese exports?

Using an augmented Chinese input–output table in which information about firm ownership and type of traded goods are explicitly reported, we show that ignoring firm heterogeneity causes embodied CO2 emissions in Chinese exports to be overestimated by 20% at the national level, with huge differences at the sector level, for 2007. This is because different types of firm that are allocated to the same sector of the conventional Chinese input–output table vary greatly in terms of market share, production technology and carbon intensity. This overestimation of export-related carbon emissions would be even higher if it were not for the fact that 80% of CO2 emissions embodied in exports of foreign-owned firms are, in fact, emitted by Chinese-owned firms upstream of the supply chain. The main reason is that the largest CO2 emitter, the electricity sector located upstream in Chinese domestic supply chains, is strongly dominated by Chinese-owned firms with very high carbon intensity.

Ofshoring de servicios en la economía española en el periodo 2000-2007

La literatura económica ha centrado la atención en el offshoring de servicios y en su efecto sobre el nivel de empleo nacional, unido a importantes críticas en relación al impacto negativo que esta estrategia provoca en términos de destrucción de empleos nacionales. En este trabajo se analiza la relevancia que tiene el offshoring de servicios en la economía española y, en concreto, en las ramas de servicios y se estudia su efecto sobre el nivel de empleo de este sector. El análisis empírico se lleva a cabo estimando una función de demanda de trabajo con elasticidad de sustitución constante (CES), incluyendo en la misma el efecto de offshoring. Este estudio se realiza para el periodo previo a la crisis, 2000-2007, a partir de los datos contenidos en las Tablas Input-Output de la Contabilidad Nacional del INE.

Economic effects of metallic corrosion in the United States.

Appendix C published in PB-279 430.

The impact of procurement-driven technological change on U.S. manufacturing productivity growth

As we enter the 21st Century, technologies originally developed for defense purposes such as computers and satellite communications appear to have become a driving force behind economic growth in the United States. Paradoxically, almost all previous econometric models suggest that the largely defense-oriented federal industrial R&D funding that helped create these technologies had no discernible effect on U.S. industrial productivity growth. This paper addresses this paradox by stressing that defense procurement as well as federal R&D expenditures were targeted to a few narrowly defined manufacturing sub-sectors that produced high tech weaponry. Analysis employing data from the NBER Manufacturing Productivity Database and the BEA' s Input Output tables then demonstrates that defense procurement policies did have significant effects on the productivity performance of disaggregated manufacturing industries because of a process of procurement-driven technological change.

Foreign direct investment, transactions linkages, and the performance of the domestic sector

Using data from the UK Census of Production, including foreign ownership data, and information from UK industry input-output tables, this paper examines whether the intensity of transactions linkages between foreign and domestic firms affects productivity growth in domestic manufacturing industries. The implications of the findings for policies promoting linkages between multinational and domestic firms in the UK economy are outlined.

Productivity growth and the structure of production

In this study, interactions between potential hierarchical value chains existing in the production structure and industry-wise productivity growths are sought. We applied generalized Chenery-Watanabe heuristics for matrix linearity maximization to triangulate the input-output incidence matrix for both Japan and the Republic of Korea, finding the potential directed flow of values spanning the industrial sectors of the basic (disaggregated) industry classifications for both countries. Sector specific productivity growths were measured by way of the Trönquvist index, using the 2000-2005 linked input-output tables for both Japan and Korea.

Vom Input zum Output

Infolge der durch die internationalen Schulvergleichstests eingeleiteten empirischen Wende in der Erziehungswissenschaft hat sich die Aufmerksamkeit vom Input schulischen Lehrens und Lernens zunehmend auf die Ergebnisse (Output) bzw. Wirkungen (Outcomes) verlagert. Die Kernfrage lautet nun: Was kommt am Ende in der Schule bzw. im Unterricht eigentlich heraus? Grundlegende Voraussetzung ergebnisorienterter Steuerung schulischen Unterrichts ist die Formulierung von Bildungsstandards. Wie Bildungsstandards mit Kompetenzmodellen und konkreten Aufgabenstellungen im Unterricht des Faches "Politik & Wirtschaft" verknüpft werden können, wird in diesem Beitrag einer genaueren Analyse unterzogen. Vor dem Hintergrund bildungstheoretischer Vorstellungen im Anschluss an Immanuel Kant kommen dabei das Literacy-Konzept der Pisa-Studie sowie die "Dokumentarische Methode" nach Karl Mannheim zur Anwendung.

Comparing Input- and Output-Oriented Measures of Technical Efficiency to Determine Local Returns to Scale in DEA Models

This paper shows how one can infer the nature of local returns to scale at the input- or output-oriented efficient projection of a technically inefficient input-output bundle, when the input- and output-oriented measures of efficiency differ.

Competitiveness of the Indonesian construction industry

Indonesia’s construction industry is important to the national economy. However, its competitiveness is considered low due to the lack of success of its development strategy and policy. A new approach known as the cluster approach is being used to make strategy and policy in order to develop a stronger, and more competitive industry. This paper discusses the layout of the Indonesian construction cluster and its competitiveness. The archival analysis research approach was used to identify the construction cluster. The analysis was based on the input-output (I/O) tables of the years 1995 and 2000, which were published by the Indonesian Central Bureau of Statistics. The results suggest that the Indonesian construction cluster consists of the industries directly involved in construction as the core, with the other related and supporting industries as the balance. The anatomy of the Indonesian construction cluster permits structural changes to happen within it. These changes depend on policies that regulate the cluster’s constituents

A Theory of How the Brain Might Work

I wish to propose a quite speculative new version of the grandmother cell theory to explain how the brain, or parts of it, may work. In particular, I discuss how the visual system may learn to recognize 3D objects. The model would apply directly to the cortical cells involved in visual face recognition. I will also outline the relation of our theory to existing models of the cerebellum and of motor control. Specific biophysical mechanisms can be readily suggested as part of a basic type of neural circuitry that can learn to approximate multidimensional input-output mappings from sets of examples and that is expected to be replicated in different regions of the brain and across modalities. The main points of the theory are: -the brain uses modules for multivariate function approximation as basic components of several of its information processing subsystems. -these modules are realized as HyperBF networks (Poggio and Girosi, 1990a,b). -HyperBF networks can be implemented in terms of biologically plausible mechanisms and circuitry. The theory predicts a specific type of population coding that represents an extension of schemes such as look-up tables. I will conclude with some speculations about the trade-off between memory and computation and the evolution of intelligence.

Integrated Environment for Launch Vehicle Telemetry Data Management

The telemetry data processing operation intended for a given mission are pre-defined by an onboard telemetry configuration, mission trajectory and overall telemetry methodology have stabilized lately for ISRO vehicles. The given problem on telemetry data processing is reduced through hierarchical problem reduction whereby the sequencing of operations evolves as the control task and operations on data as the function task. The function task Input, Output and execution criteria are captured into tables which are examined by the control task and then schedules when the function task when the criteria is being met.

The manufacturing industry in Brazil in the era of global value chains

This article presents a comprehensive and detailed overview of the international trade performance of the manufacturing industry in Brazil over the last decades, emphasizing its participation in Global Value Chains. It uses information from recent available global inputoutput tables such as WIOD (World Input-output database) and TIVA (Trade in Value Added, OECD) as well as complementary information from the GTAP 8 (Global Trade Analysis Project) database. The calculation of a broad set of value added type indicators allows a precise contextualization of the ongoing structural changes in the Brazilian industry, highlighting the relative isolation of its manufacturing sector from the most relevant international supply chains. This article also proposes a public policy discussion, presenting two case studies: the first one related to trade facilitation and the second one to preferential trade agreements. The main conclusions are twofold: first, the reduction of time delays at customs in Brazil may significantly improve the trade performance of its manufacturing industry, specially for the more capital intensive sectors which are generally the ones with greater potential to connection to global value chains; second, the extension of the concept of a “preferential trade partner” to the context of the global unbundling of production may pave the way to future trade policy in Brazil, particularly in the mapping of those partners whose bilateral trade relations with Brazil should receive greater priority by policy makers.

The manufacturing industry in Brazil in the era of global value chains

This article presents a comprehensive and detailed overview of the international trade performance of the manufacturing industry in Brazil over the last decades, emphasizing its participation in Global Value Chains. It uses information from recent available global inputoutput tables such as WIOD (World Input-output database) and TIVA (Trade in Value Added, OECD) as well as complementary information from the GTAP 8 (Global Trade Analysis Project) database. The calculation of a broad set of value added type indicators allows a precise contextualization of the ongoing structural changes in the Brazilian industry, highlighting the relative isolation of its manufacturing sector from the most relevant international supply chains. This article also proposes a public policy discussion, presenting two case studies: the first one related to trade facilitation and the second one to preferential trade agreements. The main conclusions are twofold: first, the reduction of time delays at customs in Brazil may significantly improve the trade performance of its manufacturing industry, specially for the more capital intensive sectors which are generally the ones with greater potential to connection to global value chains; second, the extension of the concept of a “preferential trade partner” to the context of the global unbundling of production may pave the way to future trade policy in Brazil, particularly in the mapping of those partners whose bilateral trade relations with Brazil should receive greater priority by policy makers

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.