Debunking Weak Sustainable Consumption : Towards Strong Sustainable Consumption Governance

Achieving sustainable consumption patterns is a crucial step on the way towards sustainability. The scientific knowledge used to decide which priorities to set and how to enforce them has to converge with societal, political, and economic initiatives on various levels: from individual household decision-making to agreements and commitments in global policy processes. The aim of this thesis is to draw a comprehensive and systematic picture of sustainable consumption and to do this it develops the concept of Strong Sustainable Consumption Governance. In this concept, consumption is understood as resource consumption. This includes consumption by industries, public consumption, and household consumption. Next to the availability of resources (including the available sink capacity of the ecosystem) and their use and distribution among the Earth’s population, the thesis also considers their contribution to human well-being. This implies giving specific attention to the levels and patterns of consumption. Methods: The thesis introduces the terminology and various concepts of Sustainable Consumption and of Governance. It briefly elaborates on the methodology of Critical Realism and its potential for analysing Sustainable Consumption. It describes the various methods on which the research is based and sets out the political implications a governance approach towards Strong Sustainable Consumption may have. Two models are developed: one for the assessment of the environmental relevance of consumption activities, another to identify the influences of globalisation on the determinants of consumption opportunities. Results: One of the major challenges for Strong Sustainable Consumption is that it is not in line with the current political mainstream: that is, the belief that economic growth can cure all our problems. So, the proponents have to battle against a strong headwind. Their motivation however is the conviction that there is no alternative. Efforts have to be taken on multiple levels by multiple actors. And all of them are needed as they constitute the individual strings that together make up the rope. However, everyone must ensure that they are pulling in the same direction. It might be useful to apply a carrot and stick strategy to stimulate public debate. The stick in this case is to create a sense of urgency. The carrot would be to articulate better the message to the public that a shrinking of the economy is not as much of a disaster as mainstream economics tends to suggest. In parallel to this it is necessary to demand that governments take responsibility for governance. The dominant strategy is still information provision. But there is ample evidence that hard policies like regulatory instruments and economic instruments are most effective. As for Civil Society Organizations it is recommended that they overcome the habit of promoting Sustainable (in fact green) Consumption by using marketing strategies and instead foster public debate in values and well-being. This includes appreciating the potential of social innovation. A countless number of such initiatives are on the way but their potential is still insufficiently explored. Beyond the question of how to multiply such approaches, it is also necessary to establish political macro structures to foster them.

Mathematical Aspects of Financial Markets with Frictions

Frictions are factors that hinder trading of securities in financial markets. Typical frictions include limited market depth, transaction costs, lack of infinite divisibility of securities, and taxes. Conventional models used in mathematical finance often gloss over these issues, which affect almost all financial markets, by arguing that the impact of frictions is negligible and, consequently, the frictionless models are valid approximations. This dissertation consists of three research papers, which are related to the study of the validity of such approximations in two distinct modeling problems. Models of price dynamics that are based on diffusion processes, i.e., continuous strong Markov processes, are widely used in the frictionless scenario. The first paper establishes that diffusion models can indeed be understood as approximations of price dynamics in markets with frictions. This is achieved by introducing an agent-based model of a financial market where finitely many agents trade a financial security, the price of which evolves according to price impacts generated by trades. It is shown that, if the number of agents is large, then under certain assumptions the price process of security, which is a pure-jump process, can be approximated by a one-dimensional diffusion process. In a slightly extended model, in which agents may exhibit herd behavior, the approximating diffusion model turns out to be a stochastic volatility model. Finally, it is shown that when agents' tendency to herd is strong, logarithmic returns in the approximating stochastic volatility model are heavy-tailed. The remaining papers are related to no-arbitrage criteria and superhedging in continuous-time option pricing models under small-transaction-cost asymptotics. Guasoni, Rásonyi, and Schachermayer have recently shown that, in such a setting, any financial security admits no arbitrage opportunities and there exist no feasible superhedging strategies for European call and put options written on it, as long as its price process is continuous and has the so-called conditional full support (CFS) property. Motivated by this result, CFS is established for certain stochastic integrals and a subclass of Brownian semistationary processes in the two papers. As a consequence, a wide range of possibly non-Markovian local and stochastic volatility models have the CFS property.

Efficient Content-based Routing, Mobility-aware Topologies, and Temporal Subspace Matching

Event-based systems are seen as good candidates for supporting distributed applications in dynamic and ubiquitous environments because they support decoupled and asynchronous many-to-many information dissemination. Event systems are widely used, because asynchronous messaging provides a flexible alternative to RPC (Remote Procedure Call). They are typically implemented using an overlay network of routers. A content-based router forwards event messages based on filters that are installed by subscribers and other routers. The filters are organized into a routing table in order to forward incoming events to proper subscribers and neighbouring routers. This thesis addresses the optimization of content-based routing tables organized using the covering relation and presents novel data structures and configurations for improving local and distributed operation. Data structures are needed for organizing filters into a routing table that supports efficient matching and runtime operation. We present novel results on dynamic filter merging and the integration of filter merging with content-based routing tables. In addition, the thesis examines the cost of client mobility using different protocols and routing topologies. We also present a new matching technique called temporal subspace matching. The technique combines two new features. The first feature, temporal operation, supports notifications, or content profiles, that persist in time. The second feature, subspace matching, allows more expressive semantics, because notifications may contain intervals and be defined as subspaces of the content space. We also present an application of temporal subspace matching pertaining to metadata-based continuous collection and object tracking.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Efficient search for statistically significant dependency rules in binary data

Analyzing statistical dependencies is a fundamental problem in all empirical science. Dependencies help us understand causes and effects, create new scientific theories, and invent cures to problems. Nowadays, large amounts of data is available, but efficient computational tools for analyzing the data are missing. In this research, we develop efficient algorithms for a commonly occurring search problem - searching for the statistically most significant dependency rules in binary data. We consider dependency rules of the form X->A or X->not A, where X is a set of positive-valued attributes and A is a single attribute. Such rules describe which factors either increase or decrease the probability of the consequent A. A classical example are genetic and environmental factors, which can either cause or prevent a disease. The emphasis in this research is that the discovered dependencies should be genuine - i.e. they should also hold in future data. This is an important distinction from the traditional association rules, which - in spite of their name and a similar appearance to dependency rules - do not necessarily represent statistical dependencies at all or represent only spurious connections, which occur by chance. Therefore, the principal objective is to search for the rules with statistical significance measures. Another important objective is to search for only non-redundant rules, which express the real causes of dependence, without any occasional extra factors. The extra factors do not add any new information on the dependence, but can only blur it and make it less accurate in future data. The problem is computationally very demanding, because the number of all possible rules increases exponentially with the number of attributes. In addition, neither the statistical dependency nor the statistical significance are monotonic properties, which means that the traditional pruning techniques do not work. As a solution, we first derive the mathematical basis for pruning the search space with any well-behaving statistical significance measures. The mathematical theory is complemented by a new algorithmic invention, which enables an efficient search without any heuristic restrictions. The resulting algorithm can be used to search for both positive and negative dependencies with any commonly used statistical measures, like Fisher's exact test, the chi-squared measure, mutual information, and z scores. According to our experiments, the algorithm is well-scalable, especially with Fisher's exact test. It can easily handle even the densest data sets with 10000-20000 attributes. Still, the results are globally optimal, which is a remarkable improvement over the existing solutions. In practice, this means that the user does not have to worry whether the dependencies hold in future data or if the data still contains better, but undiscovered dependencies.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Foreign Capital and Finland : Central government's first period of reliance on international financial markets, 1862-1938

The main objective of the study is to evaluate the Finnish central government s foreign borrowing between the years 1862 and 1938. Most of this period was characterised by deep capital market integration that bears resemblance to the liberal world financial order at the turn of the millennium. The main aim is to analyse the credit risk associated with the state and its determination by evaluating the world financial market centres perception of Finland. By doing this, the study is also expected to provide an additional dimension to Finland s political and economic history by incorporating into the research the assessments of international capital markets regarding Finland during a period that witnessed profound political and economic changes in Finnish society. The evaluation of the credit risk mainly relies on exchange-rate risk free time series of the state s foreign bonds. They have been collected from quotations in the stock exchanges in Helsinki, Hamburg, Paris and London. In addition, it investigates Finland s exposure to short-term debt and Moody s credit ratings assigned to Finland. The study emphasises the importance of the political risk. It suggests that the hey-day of the state s reliance on foreign capital markets took place during last few decades of the 19th century when Finland enjoyed a wide autonomy in the Russian Empire and prudently managed its economy, highlighted in Finland s adherence to the international gold standard. Political confrontations in Finland and, in particular, in Russia and the turbulence of the world financial system prevented the return of this beneficial position again. Through its issuance of foreign bonds the state was able to import substantial amounts of foreign capital, which was sorely needed to foster economic development in Finland. Moreover, the study argues that the state s presence in the western capital markets not only had economic benefits, but it also increased the international awareness of Finland s distinct and separate status in the Russian Empire and later underlined its position as an independent republic.

Substance flow analysis in Finland : Four case studies on N and P flows

Nitrogen (N) and phosphorus (P) are essential elements for all living organisms. However, in excess, they contribute to several environmental problems such as aquatic and terrestrial eutrophication. Globally, human action has multiplied the volume of N and P cycling since the onset of industrialization. The multiplication is a result of intensified agriculture, increased energy consumption and population growth. Industrial ecology (IE) is a discipline, in which human interaction with the ecosystems is investigated using a systems analytical approach. The main idea behind IE is that industrial systems resemble ecosystems, and, like them, industrial systems can then be described using material, energy and information flows and stocks. Industrial systems are dependent on the resources provided by the biosphere, and these two cannot be separated from each other. When studying substance flows, the aims of the research from the viewpoint of IE can be, for instance, to elucidate the ways how the cycles of a certain substance could be more closed and how the flows of a certain substance could be decreased per unit of production (= dematerialization). In Finland, N and P are studied widely in different ecosystems and environmental emissions. A holistic picture comparing different societal systems is, however, lacking. In this thesis, flows of N and P were examined in Finland using substance flow analysis (SFA) in the following four subsystems: I) forest industry and use of wood fuels, II) food production and consumption, III) energy, and IV) municipal waste. A detailed analysis at the end of the 1990s was performed. Furthermore, historical development of the N and P flows was investigated in the energy system (III) and the municipal waste system (IV). The main research sources were official statistics, literature, monitoring data, and expert knowledge. The aim was to identify and quantify the main flows of N and P in Finland in the four subsystems studied. Furthermore, the aim was to elucidate whether the nutrient systems are cyclic or linear, and to identify how these systems could be more efficient in the use and cycling of N and P. A final aim was to discuss how this type of an analysis can be used to support decision-making on environmental problems and solutions. Of the four subsystems, the food production and consumption system and the energy system created the largest N flows in Finland. For the creation of P flows, the food production and consumption system (Paper II) was clearly the largest, followed by the forest industry and use of wood fuels and the energy system. The contribution of Finland to N and P flows on a global scale is low, but when compared on a per capita basis, we are one of the largest producers of these flows, with relatively high energy and meat consumption being the main reasons. Analysis revealed the openness of all four systems. The openness is due to the high degree of internationality of the Finnish markets, the large-scale use of synthetic fertilizers and energy resources and the low recycling rate of many waste fractions. Reduction in the use of fuels and synthetic fertilizers, reorganization of the structure of energy production, reduced human intake of nutrients and technological development are crucial in diminishing the N and P flows. To enhance nutrient recycling and replace inorganic fertilizers, recycling of such wastes as wood ash and sludge could be promoted. SFA is not usually sufficiently detailed to allow specific recommendations for decision-making to be made, but it does yield useful information about the relative magnitude of the flows and may reveal unexpected losses. Sustainable development is a widely accepted target for all human action. SFA is one method that can help to analyse how effective different efforts are in leading to a more sustainable society. SFA's strength is that it allows a holistic picture of different natural and societal systems to be drawn. Furthermore, when the environmental impact of a certain flow is known, the method can be used to prioritize environmental policy efforts.

Kriminaalipolitiikan paradoksi : Tutkimuksia huumausainerikollisuudesta ja sen kontrollista Suomessa

This doctoral thesis explores the development of drug markets and drug related crime in Finland since the mid 1990s, as well as public control measures aimed at solving problems related to drug crime. The research further examines the criminal career of persons having committed drug crime, as well as their socio-economic background. The period since the mid 1990s is, on the one hand, characterized by increasing use of drugs and increasingly severe drug problems. On the other hand, this period is also characterized by intensified drug control. Also criminality associated with drugs has increased and become more severe. During this period the prevention of drug problems became a focal issue for authorities, and resources were increased for activities geared towards fighting drugs. Along with this development, Finnish drug policy has been balancing between therapeutic activities and control. A focal point in this thesis is the question how society addresses drug problems, as well as how this differs from efforts to solve other problems. Why are criminal means so readily used when dealing with drug problems; why have the police received an extended mandate to use coercive force; and why has the field for imposing administrative sanctions been extended? How has the extension of drug control affected general thinking in criminal policy? The subject matter in this thesis is approached in a criminological and criminal policy perspective. The thesis is made up of four research articles and a Summary Article. In the Summary Article the studies were placed into the Finnish research context of drug criminality and drug control as well as criminal policy. Furthermore, the author has assessed his own research location as a drug control researcher. Applying the notion of risk, an analysis was made of threats posed by drugs to society. Theoretical perspectives were also brought to the fore on how society may regulate drug problems and threats associated with them. Based on research literature and administrative documents, an analysis was made of the relation between drug related social and health policy and criminal justice control. An account was also made of the development of drug control in Finland since the mid 1990s. There has been a strong increase in control by the criminal justice system since the mid 1990s. Penalties have been made more stringent, more efficient means have been developed to trace the financial gain from the offence, opportunities for money laundering have been prevented and the police has obtained ample new powers of inquiry. New administrative measures have been directed towards drug users, such as introducing drug tests in working life, checking the applicants criminal record for certain jobs, as well as the threat of losing one s driving licence in cases where a physician has established drug addiction. In the 1990s the prevention of drug crimes and their disclosure were made part of the police s control activities nationwide. This could clearly be seen in increased criminal statistics. There are humiliating elements associated with the police s drug control that should be eliminated for the benefit of everybody. Furthermore, the criminal control is directed towards persons in a weak socio-economic position. A drug verdict may set off a marginalization process that may be very difficult to halt. Drug control is selective and generates repressive practises. The special status accorded drug problems is also revealed in the way in which the treatment of drug addicts has developed.

Finnish and Austrian Wood Markets in a Changing Environment

At present the operating environment of sawmills in Europe is changing and there are uncertainties related in raw material supply in many countries. The changes in the operating environment of roundwood markets and the effects followed by these changes have brought up several interesting issues from the viewpoint of research. Lately new factors have been influencing the roundwood markets, such as increasing interest towards wood-based energy and implementation of new energy policies as well as changes in wood trade flows that affect the domestic markets in many countries. This Master’s thesis studies the adaptation ability of Finnish roundwood markets in a changing operating environment, aiming to produce an up-to-date analysis considering new development trends. The study concentrates on the roundwood markets from the viewpoint of sawmill industry since the industry is dependent on the functioning of the markets and sawmills are highly affected by the changes on the roundwood markets. To facilitate international comparison, the study is implemented by comparing Finnish and Austrian roundwood markets and analysing changes happening in the two countries. Finland and Austria share rather similar characteristics in the roundwood market structures, forest resources and forest ownership as well as production of roundwood and sawnwood. In addition they both are big exporters of forest industry products. In this study changes in the operating environment of sawmill industry both in Finland as well as in Austria are compared to each other aiming to recognise the main similarities and differences between the countries. In addition both development possibilities as well as challenges followed by the changes are discussed. The aim of the study is to define the main challenges and possibilities confronted by the actors on the markets and also to find new perspectives to approach these. The study is implemented as a qualitative study. The theoretical framework of the study describes the operating environment of wood markets from the viewpoint of the sawmill industry and represents the effects of supply and demand on the wood markets. The primary research material of the study was gathered by interviewing high level experts of forestry and sawmill industry in both Finland and Austria. The aim was to receive as extensive country specific viewpoint from the markets as possible, hence interviewees represented different parties of the markets. After creating country-specific profiles based on the theoretical framework a cross-country comparison was implemented. As a consequence the main similarities and differences in the operating environment and on the roundwood markets of Finland and Austria were recognized. In addition the main challenges and possibilites were identified. The results of the study offer a wide analysis regarding the main similarities and differences of the wood markets of Finland and Austria and their operating environments as well as concerning challenges and possibilities faced on the markets.