The UK waste input–output table: Linking waste generation to the UK economy

Peer reviewed

The UK waste input–output table : Linking waste generation to the UK economy

Peer reviewed

Analysis of output properties of the Peroxiredoxin/Thioredoxin/Thioredoxin reductase system

Dissertação de mestrado em Bioinformática

O Modelo unput-output no planeamento de longo prazo

Doutoramento em Economia.

Inter-Connectedness In The Scottish Economy, 1998-2004

The measurement of inter-connectedness in an economy using input-output tables is not new, however much of the previous literature has not had any explicit dynamic dimension. Studies have tried to estimate the degree of inter-relatedness for an economy at a given point in time using one inputoutput table, some have compared different economies at a point in time but few have looked at the question of how inter-connectedness within an economy changes over time. The publication in 2009 of a consistent series of inputoutput tables for Scotland offers the researcher the opportunity to track changes in the degree of inter-connectedness over the seven year period 1998 to 2004. The paper is in two parts. A simple measure of inter-connectedness is introduced in the first part of the paper and applied to the Scottish tables. It is shown that although the aggregate results might appear to indicate a degree of import substitution was taking place this result is not robust to industrial disaggregation. In the second part of the paper an extraction method is applied to an eleven sector disaggregation of the Scottish economy in order to estimate how interconnectedness has changed over time for each industrial sector. It is shown that for the majority of sectors the degree of interconnectedness with the rest of the Scottish economy has grown for others, in particular Financial Services and Energy and Water Supply it has not.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Input diffusion and the evolution of production networks

What determines which inputs are initially considered and eventually adopted in the productionof new or improved goods? Why are some inputs much more prominent than others? We modelthe evolution of input linkages as a process where new producers first search for potentially usefulinputs and then decide which ones to adopt. A new product initially draws a set of 'essentialsuppliers'. The search stage is then confined to the network neighborhood of the latter, i.e., to theinputs used by the essential suppliers. The adoption decision is driven by a tradeoff between thebenefits accruing from input variety and the costs of input adoption. This has important implicationsfor the number of forward linkages that a product (input variety) develops over time. Inputdiffusion is fostered by network centrality ? an input that is initially represented in many networkneighborhoods is subsequently more likely to be adopted. This mechanism also delivers a powerlaw distribution of forward linkages. Our predictions continue to hold when varieties are aggregatedinto sectors. We can thus test them, using detailed sectoral US input-output tables. We showthat initial network proximity of a sector in 1967 significantly increases the likelihood of adoptionthroughout the subsequent four decades. The same is true for rapid productivity growth in aninput-producing sector. Our empirical results highlight two conditions for new products to becomecentral nodes: initial network proximity to prospective adopters, and technological progress thatreduces their relative price. Semiconductors met both conditions.

The Transmission of Monetary Policy in a Multi-Sector Economy

This paper constructs and estimates a sticky-price, Dynamic Stochastic General Equilibrium model with heterogenous production sectors. Sectors differ in price stickiness, capital-adjustment costs and production technology, and use output from each other as material and investment inputs following an Input-Output Matrix and Capital Flow Table that represent the U.S. economy. By relaxing the standard assumption of symmetry, this model allows different sectoral dynamics in response to monetary policy shocks. The model is estimated by Simulated Method of Moments using sectoral and aggregate U.S. time series. Results indicate 1) substantial heterogeneity in price stickiness across sectors, with quantitatively larger differences between services and goods than previously found in micro studies that focus on final goods alone, 2) a strong sensitivity to monetary policy shocks on the part of construction and durable manufacturing, and 3) similar quantitative predictions at the aggregate level by the multi-sector model and a standard model that assumes symmetry across sectors.

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.

Infiltración y erosión

Esta monografía se enmarca en el manejo de los recursos hídricos en grandes redes de riego. En ella se describe el caso del río Mendoza, en la provincia homónima, el que fuera regulado en el año 2002. Este río nace en la Cordillera de los Andes, y presenta un importante arrastre de sólidos en suspensión, los que actualmente son retenidos en gran medida por el embalse Potrerillos. Las “aguas claras" que se erogan del embalse producen problemas erosivos, los que a su vez estarían ocasionando una mayor infiltración en los canales, y con ello un incremento en la recarga de acuíferos en ciertas zonas, así como problemas derivados del ascenso de la freática en otras. Se citan procesos ocurridos en otros distritos de riego frente a la regulación de los ríos, para concluir que el del río Mendoza es un caso susceptible de sufrir ciertos per-juicios, ya señalados en la Manifestación General de Impacto Ambiental del embalse Potrerillos, los que actualmente se están presentando en la red de riego. A partir de los estudios de sedimentología en el río Mendoza, se hace un análisis técnico de los fenómenos asociados al cambio de las características físicas del agua. Luego se describen los procesos erosivos, de acuerdo con la hidráulica clásica. Se define la Eficiencia de conducción (Ec), la infiltración en canales y su importancia en distintos distritos de riego, para luego mencionar los estudios realizados en el área del río Mendoza. Se analiza el desarrollo espacial que ha tenido el oasis, la escasa programación que tuvo su traza y la antigüedad de la misma. La descripción de los suelos permite concluir acerca de la importancia de su estructura y del papel que juegan las porciones finas, aún en minoría, que integran las distintas clases texturales con respecto a la Ec. Se describen los criterios con que se distribuye el agua en Mendoza, analizándose los caudales distribuidos actualmente, para relacionarlos con los niveles freáticos. Se mencionan además distintas acciones encaradas por la provincia para mitigar los efectos de las aguas claras. El análisis de los métodos utilizados para medir la Ec, permite apreciar el estado de la ciencia al respecto. Un análisis de las ventajas y de las desventajas de los distintos métodos, y de los resultados que con ellos se obtienen, permite concluir que el método de entradas y salidas es el que mejor se adapta en Mendoza, incluyendo además aspectos metodológicos de la medición. También se concluye en que la Ec. está insuficientemente evaluada; las fracciones finas de los suelos en muchos casos gravitan más que la textura frente a la Ec; por ello, se considera que el estudio de la Ec en las distintas áreas de manejo es necesario para entender los procesos de revenición y recarga de acuíferos, y que las pérdidas administrativas pueden gravitar más que la Ec. Se recomienda continuar con los trabajos de evaluación de Ec, al ser necesarios para todas las actividades en la cuenca; se desaconseja en este río el ajuste de modelos de predicción de Ec; las características de los suelos obligan a interpretar y aplicar con criterio la bibliografía internacional, pero aún así no se pueden hacer generalizaciones acerca de de la Ec en Mendoza.

How are global value chains fragmented and extended in China's domestic production networks?

Global value chains are supported not only directly by domestic regions that export goods and services to the world market, but also indirectly by other domestic regions that provide parts, components, and intermediate services to final exporting regions. In order to better understand the nature of a country’s position and degree of participation in global value chains, we need to more fully examine the role of individual domestic regions. Understanding the domestic components of global supply chains is especially important for large developing countries like China and India, where there may be large variations in economic scale and development between domestic regions. This paper proposes a new framework for measuring domestic linkages to global value chains. This framework measures domestic linkages by endogenously embedding a country’s domestic interregional input-output (IO) table in an international IO model. Using this framework, we can more clearly describe how global production is fragmented and extended through linkages across a country’s domestic regions. This framework will also enable us to estimate how value added is created and distributed in both domestic and international segments of global value chains. For examining the validity and usefulness of this new approach, some numerical results are presented and discussed based on the 2007 Chinese interregional IO table, China customs statistics at the provincial level, and World Input-Output Tables (WIOTs).

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.

A slide scanner input for paramatrix,

"Supported in part by the Office of Naval Research. Contract no.N00014-67-A-0305-0007."

Subcellular localization determines MAP kinase signal output

The Raf-MEK-ERK MAP kinase cascade transmits signals from activated receptors into the cell to regulate proliferation and differentiation. The cascade is controlled by the Ras GTPase, which recruits Raf from the cytosol to the plasma membrane for activation. In turn, MEK, ERK, and scaffold proteins translocate to the plasma membrane for activation. Here, we examine the input-output properties of the Raf-MEK-ERK MAP kinase module in mammalian cells activated in different cellular contexts. We show that the MAP kinase module operates as a molecular switch in vivo but that the input sensitivity of the module is determined by subcellular location. Signal output from the module is sensitive to low-level input only when it is activated at the plasma membrane. This is because the threshold for activation is low at the plasma membrane, whereas the threshold for activation is high in the cytosol. Thus, the circuit configuration of the module at the plasma membrane generates maximal outputs from low-level analog inputs, allowing cells to process and respond appropriately to physiological stimuli. These results reveal the engineering logic behind the recruitment of elements of the module from the cytosol to the membrane for activation.

Undermined climate policies : a study on the impact of regulatory and financial discrimination across heterogeneous firms in China

Firms in China within the same industry but with different ownership and size have very different production functions and can face very different emission regulations and financial conditions. This fact has largely been ignored in most of the existing literature on climate change. Using a newly augmented Chinese input–output table in which information about firm size and ownership are explicitly reported, this paper employs a dynamic computable general equilibrium (CGE) model to analyze the impact of alternative climate policy designs with respect to regulation and financial conditions on heterogeneous firms. The simulation results indicate that with a business-as-usual regulatory structure, the effectiveness and economic efficiency of climate policies is significantly undermined. Expanding regulation to cover additional firms has a first-order effect of improving efficiency. However, over-investment in energy technologies in certain firms may decrease the overall efficiency of investments and dampen long-term economic growth by competing with other fixed-capital investments for financial resources. Therefore, a market-oriented arrangement for sharing emission reduction burden and a mechanism for allocating green investment is crucial for China to achieve a more ambitious emission target in the long run.