Inventory investment and GDP characteristics in OECD countries

There are very few research studies on macroeconomic inventory behaviour of various countries. It is clear that macro inventories are the results of a large number of individual microdecisions. However, we believe that it is worth analysing how inventories develop in the individual countries and why we can see different tendencies. This paper is the newest piece in a series of studies on the above subject. We use the OECD database to analyse inventory trends between 1987 and 2004 in nine of the most developed economies of the world. Annual inventory investment data are used and their connections with other components of GDP expenditure (governmental and private consumption, investment in fixed assets and foreign trade balance as well as the annual growth rate of GDP) are examined by multi-variable statistical analysis. Conclusions include the steadily decreasing tendency of inventory fluctuations, the varying periods of higher and lower rates of inventory investments and the differences of main influencing factors by country.

A magyarországi közművállalatok tehernövekedését eredményező állami intézkedések hatása. Három magyarországi víziközmű-vállalkozás GDP-megoszlásának tanulságai

A közmű-szolgáltatások fogyasztói árának általános hatósági csökkentése, a gazdasági és pénzügyi válság sújtotta magyar lakosságot "védő" kormányzati intézkedéssorozat részeként, mára szervesen betagozódott az európai közvéleményt egyaránt foglalkoztató kérdések sorába. A tagországok által eleddig szakpolitikai szinten kezelt témakör az általános politika szintjére emelkedett. Az árcsökkentéssel együtt járó, a közműcégeket az eddigieknél nagyobb mértékű tehervállalásra kényszerítő intézkedések következményei azonban egyelőre még nem ismertek. Az elemzés három magyarországi víziközmű-vállalkozás által előállított GDP megoszlását vizsgálja, az elmúlt években állandósult adóterhek következtében kialakult, valamint azok esetleges további növelése esetén bekövetkező szolgáltatói magatartás modellezésére tesz kísérletet. Az eredmények elemzése során pedig arra a következtetésre jut, hogy a vállalatokat eddigiekben terhelő elvonási arányok negatív irányba történő megváltoztatása, a jövőben fenntarthatatlan működésre kényszerítheti ezeket a vállalkozásokat.

Finite dimensional ordered vector spaces with Riesz interpolation and Effros-Shen's unimodularity conjecture

Peer reviewed

Annotated record of the detailed examination of Mn deposits from R/V Tokaidaigaku Maru II Cruise GDP-1 stations

The present paper, deals with the results of the bottom sampling. Sampling devices were a gravity corer for heat flow measurement and dredges of bucket type.

Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).

Model reduction for nonlinear aerodynamics and aeroelasticity using a Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of Computational Fluid Dynamics (CFD) solvers, for fast nonlinear aerodynamic and aeroelastic modeling. A nonlinear function is identified on selected interpolation points by
a discrete empirical interpolation method (DEIM). The flow field is then reconstructed using a least square approximation of the flow modes extracted
by proper orthogonal decomposition (POD). The aeroelastic reduce order
model (ROM) is completed by introducing a nonlinear mapping function
between displacements and the DEIM points. The proposed model is investigated to predict the aerodynamic forces due to forced motions using
a N ACA 0012 airfoil undergoing a prescribed pitching oscillation. To investigate aeroelastic problems at transonic conditions, a pitch/plunge airfoil
and a cropped delta wing aeroelastic models are built using linear structural models. The presence of shock-waves triggers the appearance of limit
cycle oscillations (LCO), which the model is able to predict. For all cases
tested, the new ROM shows the ability to replicate the nonlinear aerodynamic forces, structural displacements and reconstruct the complete flow
field with sufficient accuracy at a fraction of the cost of full order CFD
model.

Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.

Rational Function Interpolation of Electromagnetic Transfer Functions of High-Speed Interconnect Systems from Discrete Time-Domain and Frequency-Domain Data

We present new methodologies to generate rational function approximations of broadband electromagnetic responses of linear and passive networks of high-speed interconnects, and to construct SPICE-compatible, equivalent circuit representations of the generated rational functions. These new methodologies are driven by the desire to improve the computational efficiency of the rational function fitting process, and to ensure enhanced accuracy of the generated rational function interpolation and its equivalent circuit representation. Toward this goal, we propose two new methodologies for rational function approximation of high-speed interconnect network responses. The first one relies on the use of both time-domain and frequency-domain data, obtained either through measurement or numerical simulation, to generate a rational function representation that extrapolates the input, early-time transient response data to late-time response while at the same time providing a means to both interpolate and extrapolate the used frequency-domain data. The aforementioned hybrid methodology can be considered as a generalization of the frequency-domain rational function fitting utilizing frequency-domain response data only, and the time-domain rational function fitting utilizing transient response data only. In this context, a guideline is proposed for estimating the order of the rational function approximation from transient data. The availability of such an estimate expedites the time-domain rational function fitting process. The second approach relies on the extraction of the delay associated with causal electromagnetic responses of interconnect systems to provide for a more stable rational function process utilizing a lower-order rational function interpolation. A distinctive feature of the proposed methodology is its utilization of scattering parameters. For both methodologies, the approach of fitting the electromagnetic network matrix one element at a time is applied. It is shown that, with regard to the computational cost of the rational function fitting process, such an element-by-element rational function fitting is more advantageous than full matrix fitting for systems with a large number of ports. Despite the disadvantage that different sets of poles are used in the rational function of different elements in the network matrix, such an approach provides for improved accuracy in the fitting of network matrices of systems characterized by both strongly coupled and weakly coupled ports. Finally, in order to provide a means for enforcing passivity in the adopted element-by-element rational function fitting approach, the methodology for passivity enforcement via quadratic programming is modified appropriately for this purpose and demonstrated in the context of element-by-element rational function fitting of the admittance matrix of an electromagnetic multiport.

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels (< 0.5-m depth) can pose a risk to plant health and machinery before harvesting. By simulating time-series models, the risk of exceeding critical thresholds during a continuous period of time (e.g. 10 days) is described by probability levels. These simulated probabilities were interpolated spatially using universal kriging, incorporating information related to the drainage basin from a digital elevation model. The resulting map reduced model uncertainty. Three areas were defined as presenting potential risk at the end of the rainy season. These areas deserve attention with respect to water-management and land-use planning.

Long-term relationship between energy consumption and GDP in Latin America: an empirical assessment using panel data

The main objetive of this research is to evaluate the long term relationship between energy consumption and GDP for some Latin American countries in the period 1980-2009 -- The estimation has been done through the non-stationary panel approach, using the production function in order to control other sources of GDP variation, such as capital and labor -- In addition to this, a panel unit root tests are used in order to identify the non-stationarity of these variables, followed by the application of panel cointegration test proposed by Pedroni (2004) to avoid a spurious regression (Entorf, 1997; Kao, 1999)

Evaluating tests for convergence of economic series using Monte Carlo methods with an application to real GDP's per head.

Doutoramento em Economia.

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.

Skill development for innovative procurement environments in construction

The construction industry should be a priority to all governments because it impacts economically and socially on all citizens. Sector turnover in industrialised economies typically averages 8-12% of GDP. Further, construction is critical to economic growth. Recent Australian studies estimate that a 10% gain in efficiency in construction translates to a 2.5% increase in GDP Inefficiencies in the Australian construction industry have been identified by a number of recent studies modelling the building process. They have identified potential savings in time of between 25% and 40% by reducing non-value added steps in the process. A culture of reform is now emerging in the industry – one in which alternate forms of project delivery are being trialed. Government and industry have identified Alliance Contracting as a means to increase efficiency in the construction industry as part of a new innovative procurement environment. Alliance contracting requires parties to form relationships and work cooperatively to provide a more complete service. This is a significant cultural change for the construction industry, with its well-known adversarial record in traditional contracting. Alliance contracts offer enormous potential benefits, but the Australian construction industry needs to develop new skills to effectively participate in the new relationship environment. This paper describes a collaborative project identifying skill needs for clients and construction professionals to more effectively participate in an increasingly sophisticated international procurement environment. The aim of identifying these skill needs is to assist industry, government, and skill developers to prepare the Australian construction workforce for the future. The collaborating Australian team has been fortunate to secure the Australian National Museum in Canberra as its live case study. The Acton Peninsula Development is the first major building development in the world awarded on the basis of a joint alliance contract.

Best Practice Guide : Generic Overview

The construction industry is a key national economic component. It tends to be at the forefront of cyclic changes in the Australian economy. It has a significant impact, both directly and indirectly, on the efficiency and productivity of other industries. Moreover it affects everyone to a greater or lesser extent; through its products whether they are manifested in the physical infrastructure that supports the operation of the economy or through the built environment that directly impacts on the quality of life experienced by individuals. In financial terms the industry makes one of the largest contributions to the Australian economy, accounting for 4.7 per cent of GDP 1 which was worth over $30B in 20012. The construction industry is comprised of a myriad of small firms, across several important sectors including, o Residential building, o Commercial building, o Building services, o Engineering, o Infrastructure o Facilities Management o Property Development Each sector is typified by firms that have distinctive characteristics such as the number of employees, size and value of contracts, number of jobs, and so forth. It tends to be the case that firms operating in commercial building are larger than those involved in residential construction. The largest contractors are found in engineering and infrastructure, as well as in the commercial building sub-sectors. However all sectors are characterised by their reliance upon sub-contractors to carry out on-site operations. Professionals from the various design consultant groups operate across all of these sectors. This description masks one of the most significant underlying causes of inefficiency in the construction industry, namely its fragmentation. The Construction Industry chapter of the 2004 Australian Year Book3, published by the Australian Bureau of Statistics unmasks the industry’s fragmented structure, typified by the large number of operating businesses within it, the vast majority of which are small companies employing less than 5 people. It identifies over 190,000 firms, of which over 90 percent employ less than 5 people. At the other end of the spectrum, firms employing 20 or more people account for fractionally more than one percent of businesses in the industry.