4 resultados para Limited dependent variable regression

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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Dividends and their distribution decisions, being a component of the compensation of investors are a constant financial worry within companies, thus revealing one of the themes highlighted in the context of the financial literature. Study will address the factors determining the dividend policy practiced by companies listed in the Portuguese stock market. The latter will be 47 non-financial companies listed on the Euronext Lisbon during 2009 until 2011. The two samples that have been investigated include the representative of the majority of non-financial companies listed on Euronext Lisbon and the other financial companies members of the PSI 20. The methodology adopted is one of the ordinary least squares regression and the amount of dividends per share distributed was used in determining the dependent variable. In relation to the independent variables, six explanatory factors were chosen. These include profitability, stability of dividend policy, size, growth, risk and investment opportunities. The conclusion suggests that the most important factors to explain the amount of dividends distributed are profitability and stability of dividend policy. There after, growth and risk factors, as well as factors that explain the amount of dividends distributed are also relevant. The remaining variables obtained were insufficient evidence pointing to a significant effect in explaining the dividend policy of Portuguese companies in the sample. The conclusion also states that differences exist in the importance of the explanatory factors to the amount of dividends distributed between the study samples, given the differentiation of dividend policies, followed by companies from each group analyzed.

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This study analyses the determinants of the derivative instruments disclosure level by Portuguese listed companies. It is built a disclosure index to measure the disclosure level using the Consolidated Annual Reports for 2008. The hypotheses have been tested through a linear regression model using the disclosure index as the dependent variable and companies’ characteristics as independent variables. Multivariate results suggest that firm size, quality of the external auditor, belonging to PSI 20, the market to book value ratio and the percentage of capital hold by the board of directors are associated with the disclosure level.

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Guimarães, in the northwest of Portugal, is a city of strong symbolic and cultural significance and its nomination by UNESCO as world heritage, in 2001, enlarged its tourism potential. In this paper we present a few results of a survey that envisaged capturing the Guimarães residents’ perceptions of tourism impacts and their attitudes towards tourists. Specifically, one analyzes the type of relationship that exists between some socio-demographic groups and the perceived tourism impacts, as well as their socio-characteristics and the existing level of interaction between residents and tourists. The survey was implemented between January and March 2010 to a convenience sample of 540 inhabitants of the municipality of Guimarães resulting in 400 questionnaires with complete data. For this, we made use of various statistical techniques. Using a factorial analysis, we can conclude that the three factors used explain 52.3% of the variance contained in the original variables obtained from the survey. By another side, using a logit model in the analysis and taking as the dependent variable the frequent or very frequent contact with tourists, we found that only the variables referred to perceived positive impacts of tourism, education and the place of residence in urban areas have shown to be statistically significant. We are aware of the multiple ways the issue of residents’ perceptions and attitudes towards tourism can be approached and of the difficulties to get useful policy-oriented insights. This paper is a step in that trail.

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In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.