A rapidly growing share of global agricultural areas is devoted to the production of biomass for non-food purposes. The expanding non-food bioeconomy can have far-reaching social and ecological implications; yet, the non-food sector has attained little attention in land footprint studies. This paper provides the first assessment of the global cropland footprint of non-food products of the European Union (EU), a globally important region regarding its expanding bio-based economy. We apply a novel hybrid land flow accounting model, combining the biophysical trade model LANDFLOW with the multi-regional input-output model EXIOBASE. The developed hybrid approach improves the level of product and country detail, while comprehensively covering all global supply chains from agricultural production to final consumption, including highly-processed products, such as many non-food products. The results highlight the EU's role as a major processing and the biggest consuming region of cropland-based non-food products while at the same time relying heavily on imports. Two thirds of the cropland required to satisfy the EU's non-food biomass consumption are located in other world regions, particularly in China, the US and Indonesia, giving rise to potential impacts on distant ecosystems. With almost 39% in 2010, oilseeds used to produce for example biofuels, detergents and polymers represented the dominant share of the EU's non-food cropland demand. Traditional non-food biomass uses, such as fibre crops for textiles and animal hides and skins for leather products, also contributed notably (22%). Our findings suggest that if the EU Bioeconomy Strategy is to support global sustainable development, a detailed monitoring of land use displacement and spillover effects is decisive for targeted and effective EU policy making.

Interindustry transactions recorded at a macro level are simply summations of commodity shipment decisions taken at a micro level. The resulting statistical problem is to obtain minimally biased estimates of commodity flow distributions at the disaggregated level, given various forms of aggregated information. This study demonstrates the application of the entropy-maximizing paradigm in its traditional form, together with recent adaptations emerging from information theory, to the area of spatial and non-spatial input-output analysis. A clear distinction between the behavioural and statistical aspects of entropy modelling is suggested. The discussion of non-spatial input-output analysis emphasizes the rectangular and dynamic extensions of Leontief's original model, and also outlines a scheme for simple aggregation, based on a criterion of minimum loss of information. In the chapters on spatial analysis, three complementary approaches to the estimation of interregional flows are proposed. Since the static formulations cannot provide an accurate picture of the gross interregional flows between any two sectors, Leontief's dynamic framework is adapted to the problem. The study concludes by describing a hierarchical system of models to analyse feasible paths of economic development over space and time. / digitalisering@umu

The aim of the thesis is to study some of the essential consequences of the location of Algots Ltd in three municipalities (Lycksele, Norsjö and Skellefteå) in Västerbotten County in northern Sweden. The factories were established with huge subsidies from the Swedish Government which considered the location as a major effort to stimulate regional development in Västerbotten County.The study shows that the yearly working time has increased, on average, by 80 per cent for the women who received employment in one of the factories. Both the incomemult i pi i er and the employmentmult i piier effects in Västerbotten County are rather small since the intermediate goods used by the firm are produced outside the region. The study also contain cost-benefit analysis as applied to the whole economy. Primarily due to very poor private profitability, the investment has yielded negative profitability to the whole economy except in the case of the Norsjö factory. / digitalisering@umu

A simulation study consists of several steps such as data collection, coding and model verification, model validation, experimental design, output data analysis, and implementation. Our research concentrates on output data analysis. In this field, many researchers have studied how to construct confidence intervals for the mean u of a stationary stochastic process. However, the estimation of the value of a nonlinear function f(u) has not received a lot of attention in the simulation literature. Towards this goal, a batch-means-based methodology was proposed by Munoz and Glynn (1997). Their approach did not consider consistent estimators for the variance of the point estimator for f(u). This thesis, however, will consider consistent variance estimation techniques to construct confidence intervals for f(u). Specifically, we propose methods based on the combination of the delta method and nonoverlapping batch means (NBM), standardized time series (STS), or a combination of both. Our approaches are tested on moving average, autoregressive, and M/M/1 queueing processes. The results show that the resulting confidence intervals (CIs) perform often better than the CIs based on the method of Munoz and Glynn in terms of coverage, the mean of their CI half-width, and the variance of their CI half-width.

In this thesis, we first present a variance estimation technique based on the standardized time series methodology for steady-state simulations. The proposed variance estimator has competitive bias and variance compared to the existing estimators in the literature. We also present the technique of rebatching to further reduce the bias and variance of our variance estimator. Second, we present two fully sequential indifference-zone procedures to select the best system from a number of competing simulated systems when best is defined by the maximum or minimum expected performance. These two procedures have parabola shaped continuation regions rather than the triangular continuation regions employed in several papers. The rocedures we present accommodate unequal and unknown ariances across systems and the use of common random numbers. However, we assume that basic observations are independent and identically normally distributed. Finally, we present procedures for finding a set of feasible or near-feasible systems among a finite number of simulated systems in the presence of multiple stochastic constraints, especially when the number of systems or constraints is large.

The primary purpose of this dissertation is to analyze the supply and demand of energy in China by utilizing an input-output-analysis. The energy input-output table used in this dissertation was combined with other data from the Energy Statistics Yearbook of China to draw up a hybrid-unit input-output table diagram and its simulation analysis. According to the data, the shortage in China¡¦s electric-producing sector in 1997 had the strongest impact on the total output of China¡¦s economy. Over the years, electric producers have been gradually playing a vital role as China¡¦s main energy source. The analysis also pointed out that China¡¦s energy industry was insignificant prior to 1997, mainly due to government price regulation. This dissertation is therefore expected to identify a new path in the study of energy demand and supply in China.

This study use regional development and input-output analysis investigates Luchu Base¡¦s industries in the development and operation period that impact of the southern regional. The multipliers and impact analysis was performed through regional input-output analysis for Luchu Base. The publishment of Taiwan regional input-output table has been stopped since 1981. Therefore, this study estimate the southern regional input coefficient table for year 2001 using Mathematic process Method and Location Quotient Method. Then using this input coefficient table to forecast the changes of output and employment in the southern region and each prefecture or city after Luchu Base established. Finally, this study evaluates the future development of Luchu Base for regional economy. The major finding include, the key effected industries during the development period of Luchu Base which are construction correlation industries would be fabricated metal products, non-metallic mineral products, iron and steel industries, and electronic machinery and other electronic equipments industries. In operation period, the significantly economical effects industries will be Luchu Base¡¦s planning industries that are electronic products, other industrial products, and other chemical products; especially the most output effect is electronic products industry. The significantly economical effects are finance and insurance, and trade and retail industries. The establishment of Luchu Base tends to have positively economical effects for southern region in the development and operation period.

The objective of the research was to demonstrate the need, feasibility and relevance of disaggregating by income group the endogenized household sector in the Canadian Input-Output (I-O) model. Personal expenditures and revenue sources were endogenized into Agriculture Canada's I-O open model. Two models were developed, Model 1 and Model 2. Model 1 was a closed model that assumed homogeneity among households. Model 2 relaxed the homogeneity assumption. / The superiority of Model 2 was empirically demonstrated by comparing the economic indicators generated by the models. The indicators of interest were industrial output, GDP at factor cost and the number of paid jobs. A sensitivity analysis investigated the impact of changes in wages and salaries and final demand on the models. Larger differences were found between the models when wages and salaries were stimulated. As hypothesized, Model 1 underestimated the contribution of the lowest wages and salaries group by 19.9 percent and overestimated the impact of the higher wages and salaries group by 19 percent. A $1 million increase in the final demand for agricultural, agri-food and petrochemical products was also simulated. The largest impacts on industrial output occurred when agricultural production was shocked ( $3.8 million). This was followed by agri-food products ($3.2 million) and petrochemical products ( $2.7 million). While differences in the models' estimates were minimal when changes in final demand were simulated, Model 2 generated additional information on the distribution of income. / In conclusion, the results generated by the I-O model with the disaggregated household sector, Model 2, were consistent with budget data and economic theory.

Thesis (PhD (Philosophy))-- University of Western Sydney, Nepean, 1998. / "Thesis submitted for the fulfilment of the requirement of Doctor of Philosophy in quantitative methods, School of Quantitative Methods and Business Operations, Faculty of Commerce, University of Western Sydney, Nepean" Bibliography : p 233-257.

Thesis (M.S.)--Michigan State University. Mechanical Engineering, 2008. / Title from PDF t.p. (viewed on July 27, 2009) Includes bibliographical references (p. 49). Also issued in print.