7 resultados para empirical methods

em Helda - Digital Repository of University of Helsinki


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In the eighteenth century, the birth of scientific societies in Europe created a new framework for scientific cooperation. Through a new contextualist study of the contacts between the first scientific societies in Sweden and the most important science academy in Europe at the time, l Académie des Sciences in Paris, this dissertation aims to shed light on the role taken by the Swedish learned men in the new networks. It seeks to show that the academy model was related to a new idea of specialisation in science. In the course of the eighteenth century, it is argued, the study of the northern phenomena and regions offered the Swedes an important field of speciality with regard to their foreign colleagues. Although historical studies have often underlined the economic, practical undertone of eighteenth-century Swedish science, participation in fashionable scientific pursuits had also become an important scene for representation. However, the views prevailing in Europe tied civilisation and learning closely to the sunnier, southern climates, which had lead to the difficulty of portraying Sweden as a learned country. The image of the scientific North, as well as the Swedish strategies to polish the image of the North as a place for science, are analysed as seen from France. While sixteenth-century historians had preferred to put down the effects of the cold and claim a similarity of northern conditions to the others, the scientific exchange between Swedish and French researchers shows a new tendency to underline the difference of the North and its harsh climate. An explanation is sought by analysing how information about northern phenomena was used in France. In the European academies, new empirical methods had lead to a need for direct observations on different phenomena and circumstances. Rather than curiosities or objects for exoticism, the eighteenth-century depictions of the northern periphery tell about an emerging interest in the most extreme, and often most telling, examples of the workings of the invariable laws of nature. Whereas the idea of accumulating knowledge through cooperation was most manifest in joint astronomical projects, the idea of gathering and comparing data from differing places of observation appears also in other fields, from experimental philosophy to natural studies or medicine. The effects of these developments are studied and explained in connection to the Montesquieuan climate theories and the emerging pre-romantic ideas of man and society.

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Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

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A vast amount of public services and goods are contracted through procurement auctions. Therefore it is very important to design these auctions in an optimal way. Typically, we are interested in two different objectives. The first objective is efficiency. Efficiency means that the contract is awarded to the bidder that values it the most, which in the procurement setting means the bidder that has the lowest cost of providing a service with a given quality. The second objective is to maximize public revenue. Maximizing public revenue means minimizing the costs of procurement. Both of these goals are important from the welfare point of view. In this thesis, I analyze field data from procurement auctions and show how empirical analysis can be used to help design the auctions to maximize public revenue. In particular, I concentrate on how competition, which means the number of bidders, should be taken into account in the design of auctions. In the first chapter, the main policy question is whether the auctioneer should spend resources to induce more competition. The information paradigm is essential in analyzing the effects of competition. We talk of a private values information paradigm when the bidders know their valuations exactly. In a common value information paradigm, the information about the value of the object is dispersed among the bidders. With private values more competition always increases the public revenue but with common values the effect of competition is uncertain. I study the effects of competition in the City of Helsinki bus transit market by conducting tests for common values. I also extend an existing test by allowing bidder asymmetry. The information paradigm seems to be that of common values. The bus companies that have garages close to the contracted routes are influenced more by the common value elements than those whose garages are further away. Therefore, attracting more bidders does not necessarily lower procurement costs, and thus the City should not implement costly policies to induce more competition. In the second chapter, I ask how the auctioneer can increase its revenue by changing contract characteristics like contract sizes and durations. I find that the City of Helsinki should shorten the contract duration in the bus transit auctions because that would decrease the importance of common value components and cheaply increase entry which now would have a more beneficial impact on the public revenue. Typically, cartels decrease the public revenue in a significant way. In the third chapter, I propose a new statistical method for detecting collusion and compare it with an existing test. I argue that my test is robust to unobserved heterogeneity unlike the existing test. I apply both methods to procurement auctions that contract snow removal in schools of Helsinki. According to these tests, the bidding behavior of two of the bidders seems consistent with a contract allocation scheme.

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Modern-day weather forecasting is highly dependent on Numerical Weather Prediction (NWP) models as the main data source. The evolving state of the atmosphere with time can be numerically predicted by solving a set of hydrodynamic equations, if the initial state is known. However, such a modelling approach always contains approximations that by and large depend on the purpose of use and resolution of the models. Present-day NWP systems operate with horizontal model resolutions in the range from about 40 km to 10 km. Recently, the aim has been to reach operationally to scales of 1 4 km. This requires less approximations in the model equations, more complex treatment of physical processes and, furthermore, more computing power. This thesis concentrates on the physical parameterization methods used in high-resolution NWP models. The main emphasis is on the validation of the grid-size-dependent convection parameterization in the High Resolution Limited Area Model (HIRLAM) and on a comprehensive intercomparison of radiative-flux parameterizations. In addition, the problems related to wind prediction near the coastline are addressed with high-resolution meso-scale models. The grid-size-dependent convection parameterization is clearly beneficial for NWP models operating with a dense grid. Results show that the current convection scheme in HIRLAM is still applicable down to a 5.6 km grid size. However, with further improved model resolution, the tendency of the model to overestimate strong precipitation intensities increases in all the experiment runs. For the clear-sky longwave radiation parameterization, schemes used in NWP-models provide much better results in comparison with simple empirical schemes. On the other hand, for the shortwave part of the spectrum, the empirical schemes are more competitive for producing fairly accurate surface fluxes. Overall, even the complex radiation parameterization schemes used in NWP-models seem to be slightly too transparent for both long- and shortwave radiation in clear-sky conditions. For cloudy conditions, simple cloud correction functions are tested. In case of longwave radiation, the empirical cloud correction methods provide rather accurate results, whereas for shortwave radiation the benefit is only marginal. Idealised high-resolution two-dimensional meso-scale model experiments suggest that the reason for the observed formation of the afternoon low level jet (LLJ) over the Gulf of Finland is an inertial oscillation mechanism, when the large-scale flow is from the south-east or west directions. The LLJ is further enhanced by the sea-breeze circulation. A three-dimensional HIRLAM experiment, with a 7.7 km grid size, is able to generate a similar LLJ flow structure as suggested by the 2D-experiments and observations. It is also pointed out that improved model resolution does not necessary lead to better wind forecasts in the statistical sense. In nested systems, the quality of the large-scale host model is really important, especially if the inner meso-scale model domain is small.

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Governance has been one of the most popular buzzwords in recent political science. As with any term shared by numerous fields of research, as well as everyday language, governance is encumbered by a jungle of definitions and applications. This work elaborates on the concept of network governance. Network governance refers to complex policy-making situations, where a variety of public and private actors collaborate in order to produce and define policy. Governance is processes of autonomous, self-organizing networks of organizations exchanging information and deliberating. Network governance is a theoretical concept that corresponds to an empirical phenomenon. Often, this phenomenon is used to descirbe a historical development: governance is often used to describe changes in political processes of Western societies since the 1980s. In this work, empirical governance networks are used as an organizing framework, and the concepts of autonomy, self-organization and network structure are developed as tools for empirical analysis of any complex decision-making process. This work develops this framework and explores the governance networks in the case of environmental policy-making in the City of Helsinki, Finland. The crafting of a local ecological sustainability programme required support and knowledge from all sectors of administration, a number of entrepreneurs and companies and the inhabitants of Helsinki. The policy process relied explicitly on networking, with public and private actors collaborating to design policy instruments. Communication between individual organizations led to the development of network structures and patterns. This research analyses these patterns and their effects on policy choice, by applying the methods of social network analysis. A variety of social network analysis methods are used to uncover different features of the networked process. Links between individual network positions, network subgroup structures and macro-level network patterns are compared to the types of organizations involved and final policy instruments chosen. By using governance concepts to depict a policy process, the work aims to assess whether they contribute to models of policy-making. The conclusion is that the governance literature sheds light on events that would otherwise go unnoticed, or whose conceptualization would remain atheoretical. The framework of network governance should be in the toolkit of the policy analyst.

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This paper uses the Value-at-Risk approach to define the risk in both long and short trading positions. The investigation is done on some major market indices(Japanese, UK, German and US). The performance of models that takes into account skewness and fat-tails are compared to symmetric models in relation to both the specific model for estimating the variance, and the distribution of the variance estimate used as input in the VaR estimation. The results indicate that more flexible models not necessarily perform better in predicting the VaR forecast; the reason for this is most probably the complexity of these models. A general result is that different methods for estimating the variance are needed for different confidence levels of the VaR, and for the different indices. Also, different models are to be used for the left respectively the right tail of the distribution.

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This thesis studies the effect of income inequality on economic growth. This is done by analyzing panel data from several countries with both short and long time dimensions of the data. Two of the chapters study the direct effect of inequality on growth, and one chapter also looks at the possible indirect effect of inequality on growth by assessing the effect of inequality on savings. In Chapter two, the effect of inequality on growth is studied by using a panel of 70 countries and a new EHII2008 inequality measure. Chapter contributes on two problems that panel econometric studies on the economic effect of inequality have recently encountered: the comparability problem associated with the commonly used Deininger and Squire s Gini index, and the problem relating to the estimation of group-related elasticities in panel data. In this study, a simple way to 'bypass' vagueness related to the use of parametric methods to estimate group-related parameters is presented. The idea is to estimate the group-related elasticities implicitly using a set of group-related instrumental variables. The estimation results with new data and method indicate that the relationship between income inequality and growth is likely to be non-linear. Chapter three incorporates the EHII2.1 inequality measure and a panel with annual time series observations from 38 countries to test the existence of long-run equilibrium relation(s) between inequality and the level of GDP. Panel unit root tests indicate that both the logarithmic EHII2.1 inequality measure and the logarithmic GDP per capita series are I(1) nonstationary processes. They are also found to be cointegrated of order one, which implies that there is a long-run equilibrium relation between them. The long-run growth elasticity of inequality is found to be negative in the middle-income and rich economies, but the results for poor economies are inconclusive. In the fourth Chapter, macroeconomic data on nine developed economies spanning across four decades starting from the year 1960 is used to study the effect of the changes in the top income share to national and private savings. The income share of the top 1 % of population is used as proxy for the distribution of income. The effect of inequality on private savings is found to be positive in the Nordic and Central-European countries, but for the Anglo-Saxon countries the direction of the effect (positive vs. negative) remains somewhat ambiguous. Inequality is found to have an effect national savings only in the Nordic countries, where it is positive.