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.

Tiedon jakaminen tiimityössä

Knowledge-sharing in a teamwork The study examines the link between knowledge-sharing that takes place in a team and the dimensions and objectives of the team s activities. The question the study poses is: How does knowledge-sharing in a team relate to the team s activities? The exchange of knowledge is examined using knowledge-sharing networks and the conversion model, which describes the process of knowledge formation. The answer to the question is sought through four empirical articles describing the activities of a team from the viewpoint of quality, fairness, power related to knowledge management, and performance. One of the articles used in the study describes the role of networks in work life more generally. It attempts to shed light on the manner in which team-related networks operate as part of a more extensive structure of organizational networks. Finland is one of the most eager users of teamwork, if numbers are used as a yardstick. About half of all Finnish wage earners worked in teams in 2009, and comparisons show that the use of teams in Finland is above the EU average. This study focuses on so-called semi-autonomous teams, which carry out permanent work tasks. In such teams, tasks are interdependent, and teams are jointly responsible for ensuring that the work is done. Team members may also, at least to some extent, agree between themselves on how the tasks are carried out and are able to take part in the decision-making process. Such teamwork makes knowledge-sharing an important element for the team s activities. Knowledge and knowledge-sharing have become a major resource, allowing organizations to operate and even compete in today s increasingly competitive markets. A single team or a single organization cannot, however, possess all the knowledge required for carrying out the tasks assigned to it. Although it is difficult to copy the knowledge generated in an organization, it is important to share the knowledge within and between organizations. External links supply teams and organizations with important knowledge that allows them to keep their operations up-to-date and their structures well-functioning. In fact, knowledge provides teams and organizations with an intangible resource that improves their capacity to interact with their environment and to adjust to it. For this reason, it is important to examine both the internal and external knowledge-sharing taking place in a team. The findings of the study show that in terms of quality, fairness, performance and the knowledge management issues concerning a team, its social network structure is both internally and externally connected with its activities. A team structure that is internally coherent and at the same time open to external contacts, is, with certain restrictions, connected with the quality, fairness, and performance of the team. The restrictions concern differences between procedural and interactional justice, public and private sectors, and the team leaders and ordinary team members. The role of the team leader is closely connected with the management of networks that are considered valuable. The results of the study indicate that teamwork is supervisor-dominated. Thus, teamwork does not substantially strengthen the influence of individual employees as players in knowledge-transfer networks. However, ordinary team members possess important peer contacts inside the organization. Teamwork clearly allows employees to interact in a democratic manner, and here the transfer of tacit knowledge plays an important role. Keywords: teamwork, knowledge-sharing, social networks, organization

Communicative and Anticipatory Decision-making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.

Social Networks and Everyday Practices in Russia

My doctoral dissertation in sociology and Russian studies, Social Networks and Everyday Practices in Russia, employs a "micro" or "grassroots" perspective on the transition. The study is a collection of articles detailing social networks in five different contexts. The first article examines Russian birthdays from a network perspective. The second takes a look at health care to see whether networks have become obsolete in a sector that is still overwhelmingly public, but increasingly being monetarised. The third article investigates neighbourhood relations. The fourth details relationships at work, particularly from the vantage point of internal migration. The fifth explores housing and the role of networks and money both in the Soviet and post-Soviet era. The study is based on qualitative social network and interview data gathered among three groups, teachers, doctors and factory workers, in St. Petersburg during 1993-2000. Methodologically it builds on a qualitative social network approach. The study adds a critical element to the discussion on networks in post-socialism. A considerable consensus exists that social networks were vital in state socialist societies and were used to bypass various difficulties caused by endemic shortages and bureaucratic rigidities, but a more debated issue has been their role in post-socialism. Some scholars have argued that the importance of networks has been dramatically reduced in the new market economy, whereas others have stressed their continuing importance. If a common denominator in both has been a focus on networks in relation to the past, a more overlooked aspect has been the question of inequality. To what extent is access to networks unequally distributed? What are the limits and consequences of networks, for those who have access, those outside networks or society at large? My study provides some evidence about inequalities. It shows that some groups are privileged over others, for instance, middle-class people in informal access to health care. Moreover, analysing the formation of networks sheds additional light on inequalities, as it highlights the importance of migration as a mechanism of inequality, for example. The five articles focus on how networks are actually used in everyday life. The article on health care, for instance, shows that personal connections are still important and popular in post-Soviet Russia, despite the growing importance of money and the emergence of "fee for service" medicine. Fifteen of twenty teachers were involved in informal medical exchange during a two-week study period, so that they used their networks to bypass the formal market mechanisms or official procedures. Medicines were obtained through personal connections because some were unavailable at local pharmacies or because these connections could provide medicines for a cheaper price or even for free. The article on neighbours shows that "mutual help" was the central feature of neighbouring, so that the exchange of goods, services and information covered almost half the contacts with neighbours reported. Neighbours did not provide merely small-scale help but were often exchange partners because they possessed important professional qualities, had access to workplace resources, or knew somebody useful. The article on the Russian work collective details workplace-related relationships in a tractor factory and shows that interaction with and assistance from one's co-workers remains important. The most interesting finding was that co-workers were even more important to those who had migrated to the city than to those who were born there, which is explained by the specifics of Soviet migration. As a result, the workplace heavily influenced or absorbed contexts for the worker migrants to establish relationships whereas many meeting-places commonly available in Western countries were largely absent or at least did not function as trusted public meeting places to initiate relationships. More results are to be found from my dissertation: Anna-Maria Salmi: Social Networks and Everyday Practices in Russia, Kikimora Publications, 2006, see www.kikimora-publications.com.

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.

Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b-Quark Jets in pp̅ Collisions at √s=1.96 TeV

We report on a search for the standard model Higgs boson produced in association with a $W$ or $Z$ boson in $p\bar{p}$ collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb$^{-1}$. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a $b$ hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110$\gevm$ to 150$\gevm$. For a mass of 115$\gevm$ the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.