The primary objective of this study was to estimate the impact that an increase in recreational expenditures, resulting from water quality improvements of Klamath Lake, would have upon the Klamath County economy. As the sales of the economy expand to serve the needs of the recreationists, real benefits will be forthcoming to the businesses and households of the county in the forms of more business and higher incomes. To estimate the total impact of the increased volume of recreational expenditures that may be made in the economy, the economic relationships of the local economy had to be determined. Primary data were collected from business firms in the county to construct an input-output model of the county's economy. The level of recreational expenditures that would be made in the county as the water quality of the lake improved were estimated. This was done for two different stages of water quality improvement. The estimated levels of recreational expenditures were then analyzed within the input-output framework to estimate the total increase in the sales of the economy and to estimate the increase in income of households in the county. / Graduation date: 1971

Interindustry, or input-output analysis is a widely used economic tool in regional analysis. This study investigates the relative worth of alternative types of input data for such models. Primary data are defined as first-hand, or survey data; secondary data are defined as second-hand, or published data. Procurement of primary data is generally much more expensive than for secondary data. Most regional economists have long held that, in general, primary data are superior to secondary data for regional investigations. This study attempts to assess the value of primary versus secondary data in view of the wide variation in collection costs. Two recently published input-output studies for the 1958-60 Arizona economy were utilized to accomplish this goal. One model used mostly primary data; the second model was compiled entirely from secondary data sources. Following careful considerations of base-period differences, geographical overlap, and sector definitions, two models-- the ARZ and the CRB--were constructed from the two source studies so as to be commensurable for statistical comparisons. The ARZ model was derived from the source study that was compiled entirely from secondary data sources; the CRB model was compiled from the source study that used mostly primary input data. Several nonparametric statistical tests were utilized on several components of the ARZ and CRB models to test for statistical similarities and dissimilarities. In general, analyses indicate strong statistical similarity between the two derived models for aggregative I-0 characteristics such as entire matrices and output multipliers, but less similarity for less aggregative components such as sub-matrices and columns of matrices. For example, comparisons between entire technical and between interdependency matrices fail to reject the null hypothesis of no median difference at the alpha level of 5 per cent. At still more unaggregated component analysis, such as for columns within technical and interdependency columns a reasonable degree of statistical similarity persisted. One chapter (V) focuses on the two derived models as they relate to water resources planning implications for Arizona. Results are similar to those for the non-water analyses; however, in the case of weighted water multipliers the similarities between the ARZ and CRB models are remarkably close. Based on an assumed short-run change of 10 per cent in deliveries to final demand for all sectors in the economy, the models differed in predictions of induced aggregate water requirements by only 9000 acre-feet of water, or less than 2 per cent. Results from the study cast doubt on the commonly held assumption of primary-data supremacy in regional interindustry studies. Results also indicate that the most important component for regional economic analysis is the final demand for each sector rather than the interindustry flows. This follows from the narrow clustering of values for output multipliers consistently observed in regional I-0 studies, and reaffirmed in this study. Therefore, students of regional economies are advised to spend marginal resources (money, time, energy) compiling more accurate final demand vectors rather than developing more accurate endogenous interindustry flows.

In the context of the transformation toward a "green economy," issues related to natural resource use have rapidly increased in importance in European and international policy debates. The large number of studies applying economy-wide material flow analysis so far mostly produced aggregated national indicators, making the results difficult to connect to policies, which are often designed for single sectors or consumption areas. This paper provides a detailed assessment of the composition of EU's material footprint in its global context, aiming at identifying the main product groups contributing to overall material consumption and specifying the geographical sources for the raw materials required to satisfy EU's final demand. Based on multi-regional input¿output (MRIO) modeling, we apply production layer decomposition to assess supply chains and their structural changes from 1995 to 2011. The global MRIO database used in this study is EXIOBASE 3, which disaggregates 200 products and 163 industries, of which 33 represent material extraction sectors. By that means, we increase the level of detail to a degree where policies can more easily connect to. We find that the generally growing material footprint of the EU was characterized by a dramatic shift regarding the origin of raw materials, with the share of materials extracted within the EU territory falling from 68 % in 1995 to 35 % in 2011. In 2011, raw materials extracted in China to produce exports to the EU already contributed an equal share to EU's material footprint as material extraction within the EU itself. Import dependency is most critical for the material group of metal ores, with only 13 % of all metals required as inputs to EU final demand stemming from within the EU. Regarding product composition, construction was confirmed as the most important sector contributing to the material footprint, followed by the group of manufacturing products based on biomass. Materials embodied in service sector activities together contributed a quarter to the total material footprint in 2011, making services an important, but currently disregarded area for European resource policies. We also find that supply chain structures became more complex over time, with a growing part located outside the EU territory. (authors' abstract)

Material flow-based indicators play an important role in indicator sets related to green and resource-efficient growth. This paper examines the global flows of materials and the amounts of materials directly and indirectly necessary to satisfy domestic final demand in different countries world-wide. We calculate the indicator Raw Material Consumption (RMC), also referred to as Material Footprint (MF), by applying a global, multi-regional input-output (MRIO) model based on the GTAP database and extended by material extraction data. We examine world-wide patterns of material extraction and materials embodied in trade and consumption, investigating changes between 1997 and 2007. We find that flows of materials related to international trade have increased by almost 60% between 1997 and 2007. We show that the differences in Material Footprints per capita are huge, ranging from up to 100 tonnes in the rich, oil-exporting countries to values as low as 1.5 to 2 tonnes in some developing countries. We also quantify the differences between the indicators Domestic Material Consumption (DMC) and RMC, illustrating that net material exporters generally have a DMC larger than RMC, while the reverse is observed for net importers. Finally, we confirm the fact that most countries with stable or declining DMCs actually show increasing RMCs, indicating the occurrence of leakage effects, which are not fully captured by DMC. This challenges the world-wide use of DMC as a headline indicator for national material consumption and calls for the consideration of upstream material requirements of international trade flows.

Water is a prerequisite for life on our planet. Due to climate change and pollution, water availability for agricultural production, industry and households is increasingly put at risk. With agriculture being the largest water user as well as polluter worldwide, we estimate anthropogenic nitrogen and phosphorus emissions to fresh water related to global crop production at a spatial resolution level of 5 by 5 arc min and calculate the grey water footprints (GWF) related to EU-27's crop production. A multiregional input-output model is used to trace the the GWF embodied in the final consumption of crop products by the EU-27. The total GWF related to crop production in the EU-27 in 2007 was 1 × 1012 m3/year. Spain contributed about 40% to this total. Production of cereals (wheat, rice and other cereals) take the largest share, accounting for 30% of the GWF, followed by fruits (17%), vegetables (14%), and oil crops (13%). The total agricultural GWF of the EU-27 related to crop consumption was 1830 billion m3/year, which is 3700 m3/year per capita on average. Overall, the EU-27 was able to externalize about 41% of the GWF to the rest of the world through imports of crop products.

Este trabalho mostra como a teoria sobre redes sociais pode ser útil para se realizar análises de dependência intersetorial. Mais especificamente, este trabalho busca identificar os setores produtivos que exercem maior poder de influência - seja de forma positiva ou negativa sobre o sistema econômico nacional, ou seja, os setores-chave da economia brasileira. Para tanto, utiliza-se como base a matriz brasileira de insumo-produto de 1996 atualizada com dados do sistema de contas nacionais referentes ao ano de 2002. Sob uma perspectiva da teoria sobre redes sociais e com o uso do software UCINET, foram criadas duas redes que representassem as relações dos setores produtivos da economia brasileira: a primeira enfatiza as origens dos insumos utilizados pelo sistema produtivo nacional, já a segunda destaca os destinos desses insumos. Com essas redes somadas aos cálculos de índices oriundos dessa mesma teoria concluiu-se que os setores que mais impactam sobre o sistema produtivo brasileiro e, portanto, merecedores de atenção especial por parte dos formuladores de políticas econômicas são: Famílias, Agropecuária, Resto do Mundo, Refino de Petróleo e Construção Civil. Além disso, também, concluiu-se que as redes que representam os setores brasileiros são: densas, possuem baixas distâncias geodésicas, apresentam elevados coeficientes de cluster e têm graus de centralidade elevados, o que faz com que as oscilações de produção em determinado setor produtivo se propague pelo resto da economia rapidamente. / This work shows how the theory on social networks can be useful for analysis of inter dependence. More specifically, this work seeks to identify the productive sectors that have more power of influence - is a positive or negative - on the national economic system, ie the key sectors of the Brazilian economy. For both, were used as the base matrix of input-output Brazilian 1996 updated with data from the system of national accounts for the year 2002. From a perspective of the theory on social networks and with using the software UCINET, two networks were created that represented the relationship of the productive sectors of the Brazilian economy: the first emphasizes the origins of the inputs used by the national productive system and the second highlights the destinations these inputs. With these networks - added to the calculations of indices from that theory - it was concluded that the sectors that exert greater powers of influence on the Brazilian productive system, and therefore deserving of special attention by policy-makers are economic: Families, Agricultural, Rest of the World, Oil Refining and Construction. In addition, it was concluded that the networks that represent the sectors Brazilians are dense, have low geodesic distances, have high coefficients of cluster and have high degrees of centrality, which means that fluctuations of output in a productive sector spreads rapidly through the rest of the economy.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. / Bibliography: leaves BIB 1-BIB 6. / by F. Ron Jones. / Ph.D.

The main target of the thesis is analysing of short-term indirect cross-sectoral impacts of taxation of electricity, solid fuels and natural gas on particular sectors of NACE in the Czech Republic, especially impacts on production prices. The key instrument for the analysis is the short-term price model for the Czech Republic, created as a component of the thesis. A secondary target is focused on the analysis of direct impacts, especially impacts on prices and expenditures of particular sectors of NACE. Within the scope of the main target, there are five different variants of taxation. For each of them the impact of taxation of particular commodities on changes in production prices of particular sectors of NACE is simulated. Than two different variants, both of them including taxation of all commodities, are compared. The thesis includes also two hypotheses, which are going to be confirmed or disproved on the basis of obtained results. For achieving the main target the methodology of Leontief input -- output analysis was chosen (Leontief, 1966). This is the key instrument for creating short-term price model for the Czech Republic. This method is suitable especially for analysing short-term cross-sectoral impacts, however under necessary condition of no changes in current technologies, agreements and cross-sectoral relations. This condition represents strict limitation for the price model created for the thesis. Regarding scientific contribution, the main asset of this thesis is creation of macroeconomic short-term price model for the Czech Republic, which is based on methodology of Leontief input -- output analysis. The additional contribution is calculation of the short-term impacts of new environmental taxation on production prices of particular sectors of NACE. Considering available information, environmental taxes in the Czech Republic have not been analysed by Leontief input - output methodology yet. There is not also sufficient analysis of environmental taxes impacts on particular sectors of NACE in the Czech Republic. The thesis is divided to seven chapters. The first chapter focuses on introduction to environmental tax regulation issue. The second chapter presents theories and concepts of taxation impact analysis. The third chapter focuses on models and empirical research in environmental taxation area. The fourth chapter is dealing with basic practical aspects of introduction of new energy taxation in the Czech republic and presents data useful for the following analysis. The fifth chapter consists of describing of applied methodology and describing of creation of the price model. The sixth chapter summarises results of simulation of direct impact of taxation on average prices for companies and on expenditures of particular sectors of NACE. The seventh chapter presents results of cross-sectoral analysis of indirect macroeconomic impacts for all variants; the chapter includes also testing of hypotheses and comments of final results.

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