The purpose of this work was to present and apply an analytical tool to the flows of goods and income between economic agents and the environment that allows us to calculate the Environmental Gross Domestic Product (EGDP) for Brazilian Legal Amazon. In order to achieve this goal the Environmental Social Accounting Matrix (ESAM) was developed. The model was developed from the traditional Social Accounting Matrix, the Environmental Input-Output Analysis Models, and from the United Nations handbook on the System of Integrated Environmental and Economic Accountings. The EGDP was calculated from the Environmental Input-Output Analysis, since the unavailability of data did not allow the application of the model of ESAM. The flows between the economy and the environment considered were the emissions of green house gases (depreciation of natural capital) and the investment needed to return the air to the same quality it had before being polluted. The results showed that the inclusion of depreciation of natural capital in the Gross Domestic Product (GDP) and in the added value (AV) calculation for each industry of the Brazilian Legal Amazon Region diminished the AV significantly in the industries of cattle (235%), soybean (77%), and other activities of livestock and agricultural (24%). In the Rest of Brazil, the industries with the highest impact of depreciation of natural capital on AV were soybean (30%), cattle (15%) and sugarcane (13%). The total EGDP of the Brazilian Legal Amazon Region was 15% smaller than its total GDP, whereas this difference for the rest of Brazil was 1%. Considering that the GDP is a component of economic wellbeing, the results show a significant reduction in economic wellbeing due to green house gas emissions released into the air by economic activities, mainly due to land use changes. The Environmental Social Accounting Matrix Model is a useful tool to help decision makers since it offers an analytical instrument for economic behavior and the impacts of economic activities on the environment. / The purpose of this work was to present and apply an analytical tool to the flows of goods and income between economic agents and the environment that allows us to calculate the Environmental Gross Domestic Product (EGDP) for Brazilian Legal Amazon. In order to achieve this goal the Environmental Social Accounting Matrix (ESAM) was developed. The model was developed from the traditional Social Accounting Matrix, the Environmental Input-Output Analysis Models, and from the United Nations handbook on the System of Integrated Environmental and Economic Accountings. The EGDP was calculated from the Environmental Input-Output Analysis, since the unavailability of data did not allow the application of the model of ESAM. The flows between the economy and the environment considered were the emissions of green house gases (depreciation of natural capital) and the investment needed to return the air to the same quality it had before being polluted. The results showed that the inclusion of depreciation of natural capital in the Gross Domestic Product (GDP) and in the added value (AV) calculation for each industry of the Brazilian Legal Amazon Region diminished the AV significantly in the industries of cattle (235%), soybean (77%), and other activities of livestock and agricultural (24%). In the Rest of Brazil, the industries with the highest impact of depreciation of natural capital on AV were soybean (30%), cattle (15%) and sugarcane (13%). The total EGDP of the Brazilian Legal Amazon Region was 15% smaller than its total GDP, whereas this difference for the rest of Brazil was 1%. Considering that the GDP is a component of economic wellbeing, the results show a significant reduction in economic wellbeing due to green house gas emissions released into the air by economic activities, mainly due to land use changes. The Environmental Social Accounting Matrix Model is a useful tool to help decision makers since it offers an analytical instrument for economic behavior and the impacts of economic activities on the environment.

房地產業的活動被一般人認為是「火車頭產業」，探究這種未經學術嚴謹定義的說法，涵意概有兩層：其一是認為房地產業有極大的「向後關聯」效果，將可帶動相關總體經濟產業的發展。另一層涵意是指房地產業既然有帶動總體經濟繁榮成長的功能，也就意味著房地產業活動所構成的房地產景氣具有領先總體經濟景氣的特質，而為一般景氣昇沉的預期訊號。惟這種說法似乎與現實情況不合：現總體經濟景氣已有復甦跡象，但房地產業卻相對的毫無起色，因此本研究從「房地產業對總體經濟活動之影響分析」、「房地產景氣與總體經濟景氣在時間上領先、同時、落後關係之探討」兩部份，分別以較嚴謹的「產業關聯分析法」與「景氣綜合指標分析法」，來探討該說法的正確性及政策等含意，獲得「尚無充份的證據支持房地產業是火車頭產業」的結論。 　　有關政策涵義方面：房地產業的向後關聯效果不強，意味著政府如意圖以房地產業為振興經濟的逆循環政策應改變至回歸市場機制的調控，而不應有太多的政策介入。政府不必因總體經濟的不景氣而企圖刺激房地產景氣；亦無須強調總體景氣過熱而打壓房地產景氣。至於「房地產景氣與總體經濟景氣在時間上領先、同時、落後關係」部份，不論房地產綜合、各層面、基準循環指標之景氣與總體經濟綜合、構成房地產綜合景氣重要指標時間上關係比較中，我們有足夠的證據認為「房地產景氣落後總體經濟景氣」。在預測上的涵意是若干重要總體經濟指標可以用來預測房地產景氣未來的走勢。 / The fluctuation in the real estate market is of long-standing, and has evoked much discussion, particularly how the real estate activities and cycles are related to macroeconomics has been an important issue drawing tremendous attention in Taiwan. This research contains two parts : in the first part, we have applied the method of lnput-Output(I/O) analysis to identic the backward linkage of the real estate sector. In the second part, we try to use the method of composite indexes of business cycle for real estate cycle indicators, including individual activities, four different stages of real estate life cycle -- investment, construction, transaction, and utilization, to clarify the " timing " relationship between business cycle and real estate cycle. 　　Based on the economic analysis, the results of this research are following : 　　1. We have not found strong evidence supporting the important backward linkage of the real estate sector. It means, in the view of using real estate activities for pushing macroeconomics, the government should not intervene the activities of real estate industry to market mechanism due to the effect of real estate activities contribute little feedback to macroeconomics. 　　2. Our investigation reveals the macro-variables, such as GDP, M2, the index of stock market, CPI, composite index etc. , tend to be leading indicators of real estate activities over twelve months approximately. This means, in the view of forecasting, we can use certain macro-variables to forecast the trend of real estate cycle in the fliture.

La presente tesi studia la nozione di produttività dal punto di vista Classico. In primo luogo, si connette la distinzione tra produttività (productivity) e profittabilità (productiveness) a quella tra il lato della spesa e quello del valore aggiunto dell'economia, vista come un flusso circolare. In secondo luogo, si collegano vari schemi teorici alle strutture empiriche del sistema di contabilità nazionale. Si calcolano quindi sia degli indicatori dei cambiamenti della produttività fisica, utilizzando come unità dell'analisi i subsistemi in crescita, che delle misure del grado di capacità delle singole industrie di generare sovrappiú. Si ottengono ed utilizzano regole di aggregazione e procedure di riduzione al fine di tenere correttamente conto dell'eterogeneità dei mezzi di produzione prodotti. In tutta la tesi, i risultati analitici ottenuti sono corredati da applicazioni empiriche. In larga misura, tale lavoro empirico concerne l'economia italiana (1999-2007); tuttavia, alcuni risultati riguardano un insieme di paesi industrializzati (Germania, Francia, Italia, Giappone, GB e USA) nel decennio 1995-2005. / This is a study on the notion of productivity, viewed from a Classical perspective. First, the distinction between physical productivity and productiveness (i.e. profitability) is connected to the distinction between the expenditure side and value added side of the economy, seen as a circular flow. Second, a mapping of some theoretical frameworks into empirical structures of the System of National Accounts is advanced. Then, indicators of physical productivity changes with the (growing) subsystem as a unit of analysis are obtained, together with measures reflecting the degree of surplus generating capacity at the level of individual industries. Aggregation rules and reduction procedures are devised and applied to deal with the heterogeneous nature of produced means of production. All throughout the study, empirical applications of the analytical results are provided. For the most part, empirical work is referred to the case of Italy (1999-2007), though some results concern a set of advanced industrial economies (Germany, France, Italy, Japan, UK and the US) during the 1995-2005 decade.

Consumption-based environmental impact trends for the Swedish economy have been generated and analysed in order to determine their levels compared to official production-based data, and to determine whether or not the Swedish economy has decoupled growth in domestic final demand from worldwide environmental impact. Three energy resources (oil, coal and gas use, as well as their aggregate fossil fuel use) and seven emissions (CO2, CH4, N2O, SO2, NOx, CO and NMVOC, as well as the aggregate CO2 equivalents) were studied. An augmented single-regional input–output model has been deployed, with world average energy and emission intensities used for products produced abroad. A new method for updating input–output tables for years missing official input–output tables, was also developed. For each of the resources and the emissions, two time series were generated based on two different revisions of Swedish national accounts data, one for the period 1993–2003, the other for the period 2000–2005. The analysis uses a recently revised time series of environmental data from the Swedish environmental accounts, as well as recently published global environmental data from the IEA and from the EDGAR emissions database (all data from 2010 or later). An index decomposition analysis was also performed to detect the various components of the time series. For fossil fuels consumption-based data don't differ much from production-based data in total. For the greenhouse gases there is a clear increase (CO2eq emissions increase approximately 20 % from 1993–2005, mainly driven by an increase in CH4 emissions), resulting from increased emissions abroad due to the increased demand for imported products. This suggests Sweden has not decoupled economic growth from increasing greenhouse gas emissions – contrary to what the slightly decreasing official production-based UNFCCC data say. For the precursor gases (SO2, NOx, CO and NMVOC), emissions are generally decreasing, with the exception of SO2 and NOx which increase in the second time series. For all emissions studied, consumption-based data lie at much higher levels than the official production-based UNFCCC data. However, further research is needed regarding the resolution of the data of the energy use and the emissions generated abroad by the Swedish domestic final demand. Also, extension of the time series and of the environmental parameters to such things as material use is needed to find out with more certainty to what extent Swedish growth has been sustainable or not. / I den här studien har konsumtionsbaserade tidsserier på svensk fossilbränsleanvändning och på svenska utsläpp av luftföroreningar tagits fram i avsikt att jämföra dessa med de officiella produktionsbaserade tidsserierna. Syftet har varit att avgöra om det svenska samhällets påverkan på resurser och miljö ur ett konsumtionsperspektiv har minskat eller ökat över tiden, och framförallt om en frikoppling har skett mellan den svenska ekonomiska tillväxten och den påverkan Sverige har på miljön i Sverige och utomlands. Tre fossila bränslen (olja, kol, gas samt aggregatet fossila bränslen) och sju luftföroreningar (CO2, CH4, N2O, SO2, NOx, CO och NMVOC samt aggregatet CO2-ekvivalenter) har analyserats. En enkelregional input–output-modell har tagits fram, utökad med globala medelintensiteter för den produktion som sker utanför Sverige. En ny metod har också utvecklats för att generera input–output-tabeller för år där officiella sådana tabeller saknas. För samtliga energiresurser och luftföroreningar, upprättades två stycken tidsserier, baserat på två olika revisioner av ekonomiska data från nationalräkenskaperna. Den första tidsserien täcker åren 1993–2003, och den andra åren 2000–2005. Miljödata togs från nyligen reviderade tidsserier från de svenska miljöräkenskaperna samt från IEA och den internationella luftföroreningsdatabasen EDGAR (alla data reviderade 2010 eller senare). En komponentanalys utfördes också, för att identifiera olika bidragande komponenter i tidsserierna. Vad gäller fossila bränslen i sin helhet, uppstår ingen markant skillnad mellan konsumtionsbaserade och produktionsbaserade data. Vad gäller växthusgaserna kan en klar ökning urskiljas (20 procents ökning av CO2-ekvivalenter mellan 1993–2005; CH4-utsläppen har där bidragit mest), vilket beror på stigande utsläpp utomlands orsakade av ökad efterfrågan på importerade produkter. Detta antyder att den svenska tillväxten ännu inte frikopplats från ökade utsläpp av växthusgaser, vilket står i motsats till den minskning i utsläpp som de officiella produktionsbaserade siffrorna från UNFCCC-rapporteringen redovisar. För övriga luftföroreningar (SO2, NOx, CO och NMVOC), sker i allmänhet en minskning, förutom för SO2 och NOx som ökar i den andra tidsserien. Samtliga luftföroreningar ligger vidare på en betydligt högre nivå jämfört med UNFCCC-rapporteringen. Mer detaljerade studier behövs dock på den energiförbrukning och de utsläpp som svensk slutlig användning för med sig utomlands. Tidsserierna behöver också förlängas och fler miljövariabler som t.ex. materialanvändningen behöver studeras för att kunna dra säkrare slutsatser kring i vilken utsträckning som den svenska tillväxten har varit hållbar eller ej.

From the Proceedings of the 1972 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - May 5-6, 1972, Prescott, Arizona / The use of discrete conditional dependency matrices as input to stochastic decision models is examined. Some of the problems and initial assumptions involved with the construction of the above mentioned matrices are discussed. Covered in considerable detail is the transform used to relate the gamma space with the normal space. A new transform is introduced that should produce reasonable results when the record of streamflow (data) has a highly skewed distribution. Finally, the possibility of using the matrices to provide realistic inputs to a stochastic dynamic program is discussed.

Questa tesi è una raccolta di tre saggi di economia multisettoriale applicata. L'obiettivo è la progettazione di politiche economiche per il sistema educativo degli Stati Uniti. Un miglioramento delle prestazioni del sistema educativo può avere effetti positivi sullo sviluppo socio-economico del paese. Il metodo di analisi adottato è l'approccio della matrice di contabilità sociale, in inglese Social Accounting Matrix (SAM). I modelli multisettoriali basati sulla SAM estendono l'analisi input-output tradizionale ai problemi della generazione e distribuzione del reddito e della formazione della domanda finale. L'impiego di modelli multisettoriali statici e dinamici basati sulla SAM mostra che politiche per l'istruzione progettate in modo appropriato possono stimolare la produzione di capitale umano, l'attività produttiva e la formazione di reddito contribuendo, allo stesso tempo, alla stabilizzazione del deficit del governo federale degli Stati Uniti. Il primo capitolo descrive le SAM per gli Stati Uniti per gli anni 2009 e 2012 e spiega come compilare una SAM. Il secondo descrive un modello multisettoriale statico e presenta alcune politiche per l'istruzione. Il terzo descrive un modello multisettoriale dinamico e presenta alcune politiche per l'istruzione. Le politiche proposte si dimostrano adatte a contrastare crisi e recessione e possono indicare una strada verso stabilità economica e crescita. / This dissertation is a collection of three essays on applied multisectoral analysis. The aim is to design and evaluate policies for the education system of the US. Good performances in terms of education have positive externalities on the social and economic development of a country. The methodology adopted is the Social Accounting Matrix (SAM) approach, which extends traditional input-output analysis to income generation and distribution and final demand formation. Policy design and evaluation carried out through static and dynamic SAM-based multisectoral models show that well-conceived policies for education can stimulate the accumulation of human capital, production and income while contributing to the stabilization of the federal budget deficit of the US. The first chapter describes the SAMs for the US for the years 2009 and 2012 and shows how to assemble a basic SAM from readily available statistics. The second chapter discusses a static SAM-based multisectoral model and policy applications. The third chapter discusses a dynamic SAM-based multisectoral model and policy applications. The policies proposed in the second and third chapter prove to be effective in contrasting output and income downturns and can show a way for economic growth and stability.

The increasing volume of solid waste (SW), not only arising from household (Municipal SW, MSW) but also from industrial process (Industrial SW, ISW), has become a serious issue in Chinese metropolises with the economic growth, urbanization, industrialization, and increasing affluence. Growth of industry leads to the expansion of population, while the augment of demand by increasing population stimulates the industrial growth in turn, thereby increasing not only ISW generation, but also MSW generation. Therefore, in order to solve the waste problem for the construction of sustainable waste management system in a city, it is necessary to consider these two types of waste together, in which, the emphasis should be focused on waste reduction from the source. The starting point in adopting this should be a good understanding of the upstream flow of waste and accurate knowledge of the volume and composition of waste that will be generated in the future. However, due to deficient historical records and complex production process, the effective attempts at forecasting SW generation are far from enough, especially for ISW by waste category. A common approach which is based on the limited waste statistics and can be easily popularized into Chinese countries is thus urgent. This paper, therefore, attempts the construction of a systematic approach to make projections of SW generation by waste category from the following issues: (1) to develop household consumer behaviour model taking into account lifestyle of residents and project the demand of private consumption in the future; (2) to quantitatively investigate and project MSW generation fully considering the change in consumer behaviour and waste management policies; (3) to effectively evaluate the present and future industrial structure and their contributions to ISW generation among industries; (4) to carry out a scenario analysis of calculating CO2 emissions in different waste treatment options based on the projected waste quantity and composition in 2015. The approach is applied on a city level as the basic administrative unit of SW management in China. The entire framework comprises four modules-regional macro-economic module, MSW generation module, ISW generation module, and waste treatment module. Further, the study of consumption pattern conducted from the consumer behaviour model in MSW module is a prerequisite for industrial restructuring caused by change in consumption demand in ISW module. Moreover, the regional macro-economic module is to provide a means for economic structural analysis and economic forecasting, considering the influence of national GDP and socioeconomic indicators including world trade. It is found out that the regional model fits the historical records reasonably well and provides an acceptable reproduction. In the MSW generation module for estimating and projecting MSW generation, firstly the per capita total household consumption expenditure is estimated by using total consumption expenditure model; then, household consumption pattern is estimated using an extension of the linear expenditure system (LES); thereafter, MSW generation by composition is quantitatively expressed in terms of the expenditure for consumption category and waste management policies by using ordinary least squares (OLS). Then, five Chinese cities with distinct economic levels are presented by applying the module to determine the waste generation features in different regions. The research findings clearly indicate that 1) the number of variables affecting consumer behaviour in Chinese cities is not one but the integrations of a series of indicators. Aside from Shanghai, saving rate towards consumption (SAV) and natural growth rate (NAGR) are currently the two common factors. However, in Shanghai, consumer behaviour is strongly influenced by SAV and the average number of persons per household (ANPH). 2) The MSW generation model quantitatively demonstrates the linear conversion process from consumption to corresponding waste generation in all cities. For example, education and consumption of food-as the form of consumption expenditure in this research-is the source of generation of food, plastic and paper waste. Further, glass and metal waste is estimated by food expenditure in all cities. 3) Total MSW generation per unit consumption is 0.198~0.225 kg/RMB with an average value of 0.213 kg/RMB. 4) All the waste management policies analyzed in the research will provide feasible experiences or valuable lessons to other Chinese cities. 5) Volume of per capita MSW generated in 2020 will be 1.24-2.18 folds compared to that in 2008 in each city if there were no effective policies implemented advancing to diminishing waste generation. Then, for the forecasting of ISW generation of each waste category by industry, the ISW module is developed, linking three principal models-regional macro-economic model, regional input-output (IO) analysis, and ISW generation model. The approach investigates the influence of industrial restructuring on ISW generation, based on the study of consumption patterns, export composition figures and change in ISW generation coefficient. The principal priorities in the case study on Shanghai are as follows: 1) the approach provides an idea for a way to quantitatively analyze industrial restructuring by adjusting the converter that, in turn, helps assess the impact of these changes on sectoral output. 2) A sensitivity analysis describes that per yuan of increase in consumption on FOOD, CLSH, FUNI, EDUC, TRAN, HLTH and RESI induces to an average increase of 76.41, 76.16, 82.28, 106.54, 93.89, 148.30 and 292.58 g total ISW, respectively. 3) It is verified that ISW generation not only arises from economic growth but also from the onset of industrial restructuring. The unit ISW generation per gross output reduces from 0.16 to 0.14 tons/10 000 RMB as we move from 2002 to 2020. 4) It is investigated that the total volume of ISW generated in 2010, 2015 and 2020 will be 2.07, 2.83 and 4.12 times that of the 2002 levels. The total SW generation of Shanghai in 2020 will be 4.06 times of that in 2002. 5) However, if considering scenario analysis of adjusting ISW generation coefficient, the total SW generation is 1.93 times compared to 2002 and ISW is 2.18 times of MSW generation. 6) Based on our results, the industrial sectors making the biggest contribution to the production of each type of ISW can each be separately identified. Therefore, constraining specific industries or penetrating them with selective technological changes will be useful attempts on the way to meeting the objectives of overall waste reduction. Finally, in the waste treatment module, the greenhouse gas (GHG) emissions emitting from the treatment and disposal of waste, including landfill site, waste-to-energy incineration and composting are calculated, respectively. Further, based on the projection of waste quantity and composition of Shanghai in 2015, a scenario analysis is carried out as well concerning the GHG emissions from alternative treatment options. The results confirm that composting and recycling of waste before the treatment are effective attempts at reducing GHG emissions in Shanghai. Further, scenario designed as the integrated waste treatment system makes the biggest reduction of GHG emissions, as 34% as compared to current treatment options with energy recovery. In a word, this research develops the entire systematic approach investigating the upstream flow of waste generation from the viewpoint of economic growth, change in socioeconomic indicators and constitution of waste management policies, and makes a reasonable attempt at projecting SW generation of each type of waste category. Based on the results, it is suggested that for the waste reduction to promote sustainable society, government interventions including promoting green consumption, reducing extra consumption, et al. and waste policies such as increasing recycling and penetrating technological innovation in specific industries will be effective. Further, based on the forecasts of SW generation, the recycling and appropriate treatment of waste generating from municipal and industrial process can be examined from the long view. From the relationship between ISW and MSW generation, the development of industry will promote the growth of service industry and induce greater generation of recyclable items. While the recycling of these items before the waste treatment is essential for effectively reducing GHG emissions which contribute to global warming. In addition, the systematic model can be easily popularized into other Chinese cities even other Asian developing cities, thereby possibly promoting the sustainable waste management of China and Asian countries. / Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第14928号 / 工博第3155号 / 新制||工||1473(附属図書館) / 27366 / UT51-2009-M842 / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 松岡 譲, 教授 森澤 眞輔, 准教授 倉田 学児 / 学位規則第4条第1項該当

The purpose of this work was to present and apply an analytical tool to the flows of goods and income between economic agents and the environment that allows us to calculate the Environmental Gross Domestic Product (EGDP) for Brazilian Legal Amazon. In order to achieve this goal the Environmental Social Accounting Matrix (ESAM) was developed. The model was developed from the traditional Social Accounting Matrix, the Environmental Input-Output Analysis Models, and from the United Nations handbook on the System of Integrated Environmental and Economic Accountings. The EGDP was calculated from the Environmental Input-Output Analysis, since the unavailability of data did not allow the application of the model of ESAM. The flows between the economy and the environment considered were the emissions of green house gases (depreciation of natural capital) and the investment needed to return the air to the same quality it had before being polluted. The results showed that the inclusion of depreciation of natural capital in the Gross Domestic Product (GDP) and in the added value (AV) calculation for each industry of the Brazilian Legal Amazon Region diminished the AV significantly in the industries of cattle (235%), soybean (77%), and other activities of livestock and agricultural (24%). In the Rest of Brazil, the industries with the highest impact of depreciation of natural capital on AV were soybean (30%), cattle (15%) and sugarcane (13%). The total EGDP of the Brazilian Legal Amazon Region was 15% smaller than its total GDP, whereas this difference for the rest of Brazil was 1%. Considering that the GDP is a component of economic wellbeing, the results show a significant reduction in economic wellbeing due to green house gas emissions released into the air by economic activities, mainly due to land use changes. The Environmental Social Accounting Matrix Model is a useful tool to help decision makers since it offers an analytical instrument for economic behavior and the impacts of economic activities on the environment. / The purpose of this work was to present and apply an analytical tool to the flows of goods and income between economic agents and the environment that allows us to calculate the Environmental Gross Domestic Product (EGDP) for Brazilian Legal Amazon. In order to achieve this goal the Environmental Social Accounting Matrix (ESAM) was developed. The model was developed from the traditional Social Accounting Matrix, the Environmental Input-Output Analysis Models, and from the United Nations handbook on the System of Integrated Environmental and Economic Accountings. The EGDP was calculated from the Environmental Input-Output Analysis, since the unavailability of data did not allow the application of the model of ESAM. The flows between the economy and the environment considered were the emissions of green house gases (depreciation of natural capital) and the investment needed to return the air to the same quality it had before being polluted. The results showed that the inclusion of depreciation of natural capital in the Gross Domestic Product (GDP) and in the added value (AV) calculation for each industry of the Brazilian Legal Amazon Region diminished the AV significantly in the industries of cattle (235%), soybean (77%), and other activities of livestock and agricultural (24%). In the Rest of Brazil, the industries with the highest impact of depreciation of natural capital on AV were soybean (30%), cattle (15%) and sugarcane (13%). The total EGDP of the Brazilian Legal Amazon Region was 15% smaller than its total GDP, whereas this difference for the rest of Brazil was 1%. Considering that the GDP is a component of economic wellbeing, the results show a significant reduction in economic wellbeing due to green house gas emissions released into the air by economic activities, mainly due to land use changes. The Environmental Social Accounting Matrix Model is a useful tool to help decision makers since it offers an analytical instrument for economic behavior and the impacts of economic activities on the environment.

The monitoring of continuous phenomena like temperature, air pollution, precipitation, soil moisture etc. is of growing importance. Decreasing costs for sensors and associated infrastructure increase the availability of observational data. These data can only rarely be used directly for analysis, but need to be interpolated to cover a region in space and/or time without gaps. So the objective of monitoring in a broader sense is to provide data about the observed phenomenon in such an enhanced form. Notwithstanding the improvements in information and communication technology, monitoring always has to function under limited resources, namely: number of sensors, number of observations, computational capacity, time, data bandwidth, and storage space. To best exploit those limited resources, a monitoring system needs to strive for efficiency concerning sampling, hardware, algorithms, parameters, and storage formats. In that regard, this work proposes and evaluates solutions for several problems associated with the monitoring of continuous phenomena. Synthetic random fields can serve as reference models on which monitoring can be simulated and exactly evaluated. For this purpose, a generator is introduced that can create such fields with arbitrary dynamism and resolution. For efficient sampling, an estimator for the minimum density of observations is derived from the extension and dynamism of the observed field. In order to adapt the interpolation to the given observations, a generic algorithm for the fitting of kriging parameters is set out. A sequential model merging algorithm based on the kriging variance is introduced to mitigate big workloads and also to support subsequent and seamless updates of real-time models by new observations. For efficient storage utilization, a compression method is suggested. It is designed for the specific structure of field observations and supports progressive decompression. The unlimited diversity of possible configurations of the features above calls for an integrated approach for systematic variation and evaluation. A generic tool for organizing and manipulating configurational elements in arbitrary complex hierarchical structures is proposed. Beside the root mean square error (RMSE) as crucial quality indicator, also the computational workload is quantified in a manner that allows an analytical estimation of execution time for different parallel environments. In summary, a powerful framework for the monitoring of continuous phenomena is outlined. With its tools for systematic variation and evaluation it supports continuous efficiency improvement.

This dissertation is a collection of essays on challenges in international trade and international finance, which apply econometric methods to diverse data sets and relate them to economic policy questions. In times of crises, the question, whether individual countries have the ability to pursue idiosyncratic monetary policy, is important. The degree of integration and comovement between financial markets, for instance, is critical to better assess the real threat facing a country in a crisis. Also, from a macroeconomic modeling perspective, there has recently been a renewed interest in the cyclical and long-run comovement of interest rates. Hence, in a first essay, we reinvestigate the long- and short-run comovements in the G7-countries by conducting tests for cointegration, common serial correlation and codependence with nominal and real interest rates. Overall, we only find little evidence of comovements: common trends are occasionally observed, but the majority of interest rates are not cointegrated. Although some evidence for codependence of higher order can be found in the pre-Euro area sample, common cycles appear to exist only in rare cases. We argue that some earlier, more positive findings in the literature are difficult to reconcile due to differing assumptions about the underlying stochastic properties of interest rates. Hence, we conclude that they cannot be generalized for all interest rates, time periods, and reasonable alternative estimation procedures. This finding indicates that scope for individual countries to pursue stabilization policy does still exist in a globalized world. Emerging economies, in general, are much more exposed and vulnerable to crises than industrialized countries. Accordingly, stabilization policy is especially important in these countries and the selection of the best monetary regime is essential. This is why, in a second essay, we contrast two different views in the debate on official dollarization: the Mundell (1961) framework of optimum currency areas and a model on boom-bust cycles by Schneider and Tornell (2004), who take account of credit market imperfections prevalent in middle income countries. We highlight the strikingly different role of the exchange rate in the two models. While in the Mundell framework the exchange rate is expected to smooth the business cycle, the second model predicts the exchange rate to play an amplifying role. We empirically evaluate both models for eight highly dollarized Central American economies. We document the existence of credit market imperfections and find that shocks from the exchange rate indeed amplify business cycles in these countries. Using a new method proposed by Cubadda (1999 and 2007), we furthermore test for cyclical comovement and reject the hypothesis that the selected countries form an optimum currency area with the United States according to the Mundell definition. In the context of the recent global crisis, globalization and vertical integration in particular were often blamed for being the cause for the severe trade crisis. For that reason, in the essay that contributes to the trade literature, we analyze the role of international supply chains in explaining the long-run trade elasticity and its short-term volatility in the context of the recent trade collapse. We adopt an empirical strategy based on two steps: first, stylized facts on long- and short-term trade elasticity are derived from exploratory analysis and formal modeling on a large and diversified sample of countries. Then, we derive observations of interrelated input-output matrices for a demonstrative sub-set of countries. We find evidence for two supply chain related factors to explain the overshooting of trade elasticity during the 2008-2009 trade collapse: the composition and the bullwhip effect. However, evidence for a magnification effect could not be found. Overall, we do not accept the hypothesis that international supply chains explain all by themselves the changes in trade-income elasticity.