Deriving CGE Baselines from Macro-economic Projections

Quantitative policy analysts are usually confronted with the problem to derive a base-line scenario that reflects the most likely state of an economy in a future year. The methods used in practice to derive such a base-line scenarios are heterogeneous and range from the usage of the last observable year to complete and consistent estimation procedures. In the case of general equilibrium (CGE) analyses, the Scenar2020 project (European Commission 2006a) is one example how projections of macro-economic indicators (exogenous drivers) are used to construct the base-line as a model scenario: Starting from a calibrated version, exogenous variables are modified until macro-economic projections are met. However, numerous projections refer to economic indicators which are endogenous variables within the CGE framework, such as gross domestic product (GDP), market prices, or produced quantities. To investigate methods that allow integrating projections for endogenous CGE variables is the main topic of this study. Our starting point is the work by Arndt et al (2002), where entropy-based (Golan et al 1996) techniques are employed for the estimation of behavioural parameters by fitting a CGE model to time series on endogenous variables. Following this concept, we investigate a method to fit a CGE´s parameters and endogenous variables to market- and macro-economic projections from major research institutes.general equilibrium model, baseline construction, parameter estimation, macro-economic projections, Research Methods/ Statistical Methods,

Local ensemble transform Kalman filter, a fast non-stationary control law for adaptive optics on ELTs: theoretical aspects and first simulation results

We propose a new algorithm for an adaptive optics system control law, based on the Linear Quadratic Gaussian approach and a Kalman Filter adaptation with localizations. It allows to handle non-stationary behaviors, to obtain performance close to the optimality defined with the residual phase variance minimization criterion, and to reduce the computational burden with an intrinsically parallel implementation on the Extremely Large Telescopes (ELTs).Comment: This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/oe/ . Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under la

Regional Social Accounting Matrices for the EU27 (SAMNUTS2)

Agricultural polices in the EU are increasingly targeting not only the agricultural sector but also other economic branches. The indirect effects of these policies, as the rural development ones, might be as important as the direct ones, mainly on factor markets as labour. In addition, in order to better scale the adopted agricultural measures, policy makers are devoting more attention to the regionalized impacts of these policies. For these reasons, a pure partial-equilibrium agricultural model is not enough to account the effects of the EU agricultural policies. The development of regionalized Computable General Equilibrium models and the linkages with already developed regionalized agricultural partial equilibrium models is a fundamental step for agricultural economists. The greatest challenge to build a regional general equilibrium model for all EU27 NUTS2 regions is the database construction. This work show the main steps needed to construct such a database, called SAMNUTS2JRC.J.4-Agriculture and Life Sciences in the Econom

An Inventory of Datasets for the Compilation of Regional Social Accounting Matrices for the EU

Due to the ever-increasing demand for model-based analyses of regional development policies in a multi-sector context, in 2009 the Institute for Prospective Technological Studies (IPTS) launched a project on the compilation of regional Social Accounting Matrices (SAM) for the NUTS2 regions of the EU (IOTNUTS2). The SAMs cover the time span between 2000 and 2005. This database shall permit general equilibrium analyses of policies like reforestation programmes, the promotion of investment in agro-tourism or environmental services, and the support for the production of renewable energy by farming enterprises, and, more generally, it will permit the evaluation of the rural development pillar of the European Common Agricultural Policy. Such measures primarily target the agricultural sector, but are likely to have an impact on other economic sectors and aggregate regional income, depending on the regional economic structure and the dominance of agriculture. Addressing regional heterogeneity requires multi-sector data on a sub-national scale. Such datasets are usually not sufficiently detailed, if available at all, which gave rise to numerous non-survey methods to generate regional Input-Output tables based on combinations of available regional indicators and national datasets (e.g. Location Quotients, GRIT methods). One particular challenge encountered during the IOTNUTS2 project was the high level of sectoral aggregation in regional branch accounts provided by ESTAT, where agriculture, forestry, and fisheries are merged for example. Given the interest in spillover effects of dominantly agricultural policies, more detailed information was required. Therefore, statistical organisations of the 27 EU Member States were contacted and the results of previous projects on regional databases were screened. This paper gives an overview of the compiled inventory on regional datasets for EU27, starting with the target structure of the database and the available national and regional datasets from ESTAT. Based on this, we discuss the datasets obtained from national statistical departments (NSO) and from previous projects with comparable aims. In general, we achieved a significant informational gain in comparison to the exclusive use of ESTAT datasets for several Member States although for some (i.e. Bulgaria) it was not as large as initially expected. Furthermore, we used the obtained NSO data to test the reliability of non-survey methods for the combination of national and regional datasets. It appeared that forestry, mining/quarrying, and fuel industries in particular displayed substantial deviations between derived indicators and those obtained from NSO, namely intermediate demand and gross output. For other branches, information could either be obtained (e.g. agriculture) or derived indicators proved to be close to the NSO values (most service sectors). In general, we conclude that for the majority of economic sectors considered, non-survey methods can generate reliable substitutes for otherwise collected indicators, but not for some critical branches which are usually concentrated in some regions and may dominate the regional economic structure (forestry, mining, fisheries). This result can be helpful for future projects with comparable objectives as we suggest that instead of attempting to sample economy-wide datasets, a focus on the mentioned critical sectors would provide higher marginal informational gains. The data collected from all the different sources are firstly utilized to populate national Input-Output tables for the EU 27 Member States. These matrices are then balanced following standard cross-entropy methods. These tables, with the suitable level of disaggregation, could be utilized as the starting point to update the EU Input-Output tables that IPTS provided to the GTAP Consortium.JRC.J.5-Agriculture and Life Sciences in the Econom

Non-invasive monitoring and control in silicon photonics by CMOS integrated electronics

As photonics breaks away from today's device level toward large scale of integration and complex systems-on-a-chip, concepts like monitoring, control and stabilization of photonic integrated circuits emerge as new paradigms. Here, we show non-invasive monitoring and feedback control of high quality factor silicon photonics resonators assisted by a transparent light detector directly integrated inside the cavity. Control operations are entirely managed by a CMOS microelectronic circuit, hosting many parallel electronic read-out channels, that is bridged to the silicon photonics chip. Advanced functionalities, such as wavelength tuning, locking, labeling and swapping are demonstrated. The non-invasive nature of the transparent monitor and the scalability of the CMOS read-out system offer a viable solution for the control of arbitrarily reconfigurable photonic integrated circuits aggregating many components on a single chip

Automated routing and control of silicon photonic switch fabrics

Automatic reconfiguration and feedback controlled routing is demonstrated in an 8×8 silicon photonic switch fabric based on Mach-Zehnder interferometers. The use of non-invasive Contactless Integrated Photonic Probes (CLIPPs) enables real-time monitoring of the state of each switching element individually. Local monitoring provides direct information on the routing path, allowing an easy sequential tuning and feedback controlled stabilization of the individual switching elements, thus making the switch fabric robust against thermal crosstalk, even in the absence of a cooling system for the silicon chip. Up to 24 CLIPPs are interrogated by a multichannel integrated ASIC wire-bonded to the photonic chip. Optical routing is demonstrated on simultaneous WDM input signals that are labelled directly on-chip by suitable pilot tones without affecting the quality of the signals. Neither preliminary circuit calibration nor lookup tables are required, being the proposed control scheme inherently insensible to channels power fluctuations

Stress polishing demonstrator for ELT M1 segments and industrialisation

After two years of research and development under ESO support, LAM and Thales SESO present the results of their experiment for the fast and accurate polishing under stress of ELT 1.5 meter segments as well as the industrialization approach for mass production. Based on stress polishing, this manufacturing method requires the conception of a warping harness able to generate extremely accurate bending of the optical surface of the segments during the polishing. The conception of the warping harness is based on finite element analysis and allowed a fine tuning of each geometrical parameter of the system in order to fit an error budget of 25nm RMS over 300μm of bending peak to valley. The optimisation approach uses the simulated influence functions to extract the system eigenmodes and characterise the performance. The same approach is used for the full characterisation of the system itself. The warping harness has been manufactured, integrated and assembled with the Zerodur 1.5 meter segment on the LAM 2.5meter POLARIS polishing facility. The experiment consists in a cross check of optical and mechanical measurements of the mirrors bending in order to develop a blind process, ie to bypass the optical measurement during the final industrial process. This article describes the optical and mechanical measurements, the influence functions and eigenmodes of the system and the full performance characterisation of the warping harness

Tracking by 3D Model Estimation of Unknown Objects in Videos

Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to guide and improve 2D tracking with an explicit object representation, namely the textured 3D shape and 6DoF pose in each video frame. Our representation tackles a complex long-term dense correspondence problem between all 3D points on the object for all video frames, including frames where some points are invisible. To achieve that, the estimation is driven by re-rendering the input video frames as well as possible through differentiable rendering, which has not been used for tracking before. The proposed optimization minimizes a novel loss function to estimate the best 3D shape, texture, and 6DoF pose. We improve the state-of-the-art in 2D segmentation tracking on three different datasets with mostly rigid objects