921 resultados para Growth Models (economics)


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Väitöskirjassani tarkastelen informaatiohyödykkeiden ja tekijänoikeuksien taloustiedettä kahdesta eri perspektiivistä. Niistä ensimmäinen kuuluu endogeenisen kasvuteorian alaan. Väitöskirjassani yleistän ”pool of knowledge” -tyyppisen endogeenisen kasvumallin tilanteeseen, jossa patentoitavissa olevalla innovaatiolla on minimikoko, ja jossa uudenlaisen tuotteen patentoinut yritys voi menettää monopolinsa tuotteeseen jäljittelyn johdosta. Mallin kontekstissa voidaan analysoida jäljittelyn ja innovaatioilta vaaditun ”minimikoon” vaikutuksia hyvinvointiin ja talouskasvuun. Kasvun maksimoiva imitaation määrä on mallissa aina nolla, mutta hyvinvoinnin maksimoiva imitaation määrä voi olla positiivinen. Talouskasvun ja hyvinvoinnin maksimoivalla patentoitavissa olevan innovaation ”minimikoolla” voi olla mikä tahansa teoreettista maksimia pienempi arvo. Väitöskirjani kahdessa jälkimmäisessä pääluvussa tarkastelen informaatiohyödykkeiden kaupallista piratismia mikrotaloustieteellisen mallin avulla. Informaatiohyödykkeistä laittomasti tehtyjen kopioiden tuotantokustannukset ovat pienet, ja miltei olemattomat silloin kun niitä levitetään esimerkiksi Internetissä. Koska piraattikopioilla on monta eri tuottajaa, niiden hinnan voitaisiin mikrotaloustieteen teorian perusteella olettaa laskevan melkein nollaan, ja jos näin kävisi, kaupallinen piratismi olisi mahdotonta. Mallissani selitän kaupallisen piratismin olemassaolon olettamalla, että piratismista saatavan rangaistuksen uhka riippuu siitä, kuinka monille kuluttajille piraatti tarjoaa laittomia hyödykkeitä, ja että se siksi vaikuttaa piraattikopioiden markkinoihin mainonnan kustannuksen tavoin. Kaupallisten piraattien kiinteiden kustannusten lisääminen on mallissani aina tekijänoikeuksien haltijan etujen mukaista, mutta ”mainonnan kustannuksen” lisääminen ei välttämättä ole, vaan se saattaa myös alentaa laillisten kopioiden myynnistä saatavia voittoja. Tämä tulos poikkeaa vastaavista aiemmista tuloksista sikäli, että se pätee vaikka tarkasteltuihin informaatiohyödykkeisiin ei liittyisi verkkovaikutuksia. Aiemmin ei-kaupallisen piratismin malleista on usein johdettu tulos, jonka mukaan informaatiohyödykkeen laittomat kopiot voivat kasvattaa laillisten kopioiden myynnistä saatavia voittoja jos laillisten kopioiden arvo niiden käyttäjille riippuu siitä, kuinka monet muut kuluttajat käyttävät samanlaista hyödykettä ja jos piraattikopioiden saatavuus lisää riittävästi laillisten kopioiden arvoa. Väitöskirjan viimeisessä pääluvussa yleistän mallini verkkotoimialoille, ja tutkin yleistämäni mallin avulla sitä, missä tapauksissa vastaava tulos pätee myös kaupalliseen piratismiin.

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Transforming growth factor β signalling through Smad3 in allergy Allergic diseases, such as atopic dermatitis, asthma, and contact dermatitis are complex diseases influenced by both genetic and environmental factors. It is still unclear why allergy and subsequent allergic disease occur in some individuals but not in others. Transforming growth factor (TGF)-β is an important immunomodulatory and fibrogenic factor that regulates cellular processes in injured and inflamed skin. TGF-β has a significant role in the regulation of the allergen-induced immune response participating in the development of allergic and asthmatic inflammation. TGF-β is known to be an immunomodulatory factor in the progression of delayed type hypersensitivity reactions and allergic contact dermatitis. TGF-β is crucial in regulating the cellular responses involved in allergy, such as differentiation, proliferation and migration. TGF-β signals are delivered from the cytoplasm to the nucleus by TGF-β signal transducers called Smads. Smad3 is a major signal transducer in TGF-β -signalling that controls the expression of target genes in the nucleus in a cell-type specific manner. The role of TGF-β-Smad3 -signalling in the immunoregulation and pathophysiology of allergic disorders is still poorly understood. In this thesis, the role of TGF-β-Smad -signalling pathway using Smad3 -deficient knock out mice in the murine models of allergic diseases; atopic dermatitis, asthma and allergic contact reactions, was examined. Smad3-pathway regulates allergen induced skin inflammation and systemic IgE antibody production in a murine model atopic dermatitis. The defect in Smad3 -signalling decreased Th2 cytokine (IL-13 and IL-5) mRNA expression in the lung, modulated allergen induced specific IgG1 response, and affected mucus production in the lung in a murine model of asthma. TGF-β / Smad3 -signalling contributed to inflammatory hypersensitivity reactions and disease progression via modulation of chemokine and cytokine expression and inflammatory cell recruitment, cell proliferation and regulation of the specific antibody response in a murine model of contact hypersensitivity. TGF-β modulates inflammatory responses - at least partly through the Smad3 pathway - but also through other compensatory, non-Smad-dependent pathways. Understanding the effects of the TGF-β signalling pathway in the immune system and in disease models can help in elucidating the multilevel effects of TGF-β. Unravelling the mechanisms of Smad3 may open new possibilities for treating and preventing allergic responses, which may lead to severe illness and loss of work ability. In the future the Smad3 signalling pathway might be a potential target in the therapy of allergic diseases.

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Research on business growth has been criticized for methodological weaknesses. We present a mediated moderation growth model as a new methodological approach. We hypothesized that small business managers' age negatively affects business growth through focus on opportunities. We sampled 201 small business managers and obtained firm performance data over 5 years, resulting in 836 observations. Growth modeling showed systematic differences in firm performance trajectories. These differences could be explained by modeling focus on opportunities as a mediator of the relationship between small business managers' age and business growth. The study illustrates how mediation models can be tested using growth modeling.

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Query incentive networks capture the role of incentives in extracting information from decentralized information networks such as a social network. Several game theoretic tilt:Kids of query incentive networks have been proposed in the literature to study and characterize the dependence, of the monetary reward required to extract the answer for a query, on various factors such as the structure of the network, the level of difficulty of the query, and the required success probability.None of the existing models, however, captures the practical andimportant factor of quality of answers. In this paper, we develop a complete mechanism design based framework to incorporate the quality of answers, in the monetization of query incentive networks. First, we extend the model of Kleinberg and Raghavan [2] to allow the nodes to modulate the incentive on the basis of the quality of the answer they receive. For this qualify conscious model. we show are existence of a unique Nash equilibrium and study the impact of quality of answers on the growth rate of the initial reward, with respect to the branching factor of the network. Next, we present two mechanisms; the direct comparison mechanism and the peer prediction mechanism, for truthful elicitation of quality from the agents. These mechanisms are based on scoring rules and cover different; scenarios which may arise in query incentive networks. We show that the proposed quality elicitation mechanisms are incentive compatible and ex-ante budget balanced. We also derive conditions under which ex-post budget balance can beachieved by these mechanisms.

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First, in Essay 1, we test whether it is possible to forecast Finnish Options Index return volatility by examining the out-of-sample predictive ability of several common volatility models with alternative well-known methods; and find additional evidence for the predictability of volatility and for the superiority of the more complicated models over the simpler ones. Secondly, in Essay 2, the aggregated volatility of stocks listed on the Helsinki Stock Exchange is decomposed into a market, industry-and firm-level component, and it is found that firm-level (i.e., idiosyncratic) volatility has increased in time, is more substantial than the two former, predicts GDP growth, moves countercyclically and as well as the other components is persistent. Thirdly, in Essay 3, we are among the first in the literature to seek for firm-specific determinants of idiosyncratic volatility in a multivariate setting, and find for the cross-section of stocks listed on the Helsinki Stock Exchange that industrial focus, trading volume, and block ownership, are positively associated with idiosyncratic volatility estimates––obtained from both the CAPM and the Fama and French three-factor model with local and international benchmark portfolios––whereas a negative relation holds between firm age as well as size and idiosyncratic volatility.

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In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

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This study explores the role and nature of knowledge management (KM) in small and medium-sized companies (SMEs). Even though the role of knowledge as a competitive advantage is commonly recognized in the SME sector, almost no attention has been paid to the managing and developing of knowledge in SMEs. This thesis consists of three different sub-studies that were reported in four individual essays. The results of the questionnaire study indicate that nearly all companies that responded to the questionnaire (N = 108) found intangible assets, i.e. knowledge resources to be their main source of competitive advantage. However, only less than a third of the companies actively deal with knowledge management. The results also indicate a significant correlation between activity in knowledge management and sustainable organic growth of the company. The interview study (N = 10) explored the context and motives of the SMEs for managing their intangible assets, and the concrete practices of knowledge management. It turned out that KM facilitated change management, clarification of the vision and new strategy formulation. All the interviewed companies were aiming at improved innovation process, new ways of doing business and attaining an increased “knowledge focus” in their business. Nearly all also aspired to grow significantly. Thus, KM provides a strategy for these SMEs to guarantee their survival and sustainability in the turbulent markets. The action research was a process to assess and develop intangible resources in three companies. The experienced benefits were the clarification of future focus and strategy, creation of a common language to discuss strategic issues within the company, as well as improved balance of different categories of intangible assets. After the process all the case companies had developed in the chosen key areas. Thus, by systematic knowledge management the implementation of new strategic orientation (knowledge focusing) was facilitated. The findings can be summarized in two main points. First, knowledge management seems to serve the purpose of change, renewal and new strategic orientation in the SMEs. It also seems to be closely related to organic growth and innovation. All of these factors can be considered dimensions of entrepreneurship. Second, the conscious development of intangible assets can increase the balance of different categories of intangible assets and the overall knowledge focusing of business. In the case companies, this in turn facilitated the path to the improved overall performance.

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There has been considerable discussion in the literature about the relative merits of shareholder value management and stakeholder value management, but relatively little empirical research has been reported concerning the relationship between these types of management and financial performance. The present study puts forward a hypothesis that true shareholder value management also encompasses stakeholder value management. This combination of shareholder/stakeholder value management is hypothesised to be associated with superior financial performance and sales growth. Using a sample of chief financial officers' ratings of the contemporary management accounting techniques economic value added and the balanced scorecard to represent the two management types, the study found evidence in support of the hypothesis.

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This study examined the effects of the Greeks of the options and the trading results of delta hedging strategies, with three different time units or option-pricing models. These time units were calendar time, trading time and continuous time using discrete approximation (CTDA) time. The CTDA time model is a pricing model, that among others accounts for intraday and weekend, patterns in volatility. For the CTDA time model some additional theta measures, which were believed to be usable in trading, were developed. The study appears to verify that there were differences in the Greeks with different time units. It also revealed that these differences influence the delta hedging of options or portfolios. Although it is difficult to say anything about which is the most usable of the different time models, as this much depends on the traders view of the passing of time, different market conditions and different portfolios, the CTDA time model can be viewed as an attractive alternative.

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This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

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This study evaluates three different time units in option pricing: trading time, calendar time and continuous time using discrete approximations (CTDA). The CTDA-time model partitions the trading day into 30-minute intervals, where each interval is given a weight corresponding to the historical volatility in the respective interval. Furthermore, the non-trading volatility, both overnight and weekend volatility, is included in the first interval of the trading day in the CTDA model. The three models are tested on market prices. The results indicate that the trading-time model gives the best fit to market prices in line with the results of previous studies, but contrary to expectations under non-arbitrage option pricing. Under non-arbitrage pricing, the option premium should reflect the cost of hedging the expected volatility during the option’s remaining life. The study concludes that the historical patterns in volatility are not fully accounted for by the market, rather the market prices options closer to trading time.

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A diffusion/replacement model for new consumer durables designed to be used as a long-term forecasting tool is developed. The model simulates new demand as well as replacement demand over time. The model is called DEMSIM and is built upon a counteractive adoption model specifying the basic forces affecting the adoption behaviour of individual consumers. These forces are the promoting forces and the resisting forces. The promoting forces are further divided into internal and external influences. These influences are operationalized within a multi-segmental diffusion model generating the adoption behaviour of the consumers in each segment as an expected value. This diffusion model is combined with a replacement model built upon the same segmental structure as the diffusion model. This model generates, in turn, the expected replacement behaviour in each segment. To be able to use DEMSIM as a forecasting tool in early stages of a diffusion process estimates of the model parameters are needed as soon as possible after product launch. However, traditional statistical techniques are not very helpful in estimating such parameters in early stages of a diffusion process. To enable early parameter calibration an optimization algorithm is developed by which the main parameters of the diffusion model can be estimated on the basis of very few sales observations. The optimization is carried out in iterative simulation runs. Empirical validations using the optimization algorithm reveal that the diffusion model performs well in early long-term sales forecasts, especially as it comes to the timing of future sales peaks.