Análisis de la información financiera en torno al informe del auditor de las empresas del MILA

In the current enterprise context, the generation of transparent and good-quality financial and non-financial information is fundamental for adequate decision-making. Considering this context, this paper aims at evaluating the relationship between an audit report and the variation of the financial information of the companies who have a participation in the stock exchanges markets of the MILA countries over the period 2012- 2018. A quantitative approach was used in this investigation, using Logit and Probit models. As results, the outlined model predicts, to a great extent, that an auditor’s unqualified opinion translates into financial information variables’ positive behavior. Also, a great correlation between the audit firm, especially if it is a Big Four, and company income was found, which translates into favorable audit reports.

Evaluating Perception of Sustainability Initiatives Invested in the Coastal Area of Versilia, Italy

Nowadays, following the increased interest and need for the issue of sustainability, tourist destinations are called upon to promote sustainable tourism development through the implementation of investments and initiatives. Despite the investments by the destinations, how are these perceived by tourists and residents? Based on this, this paper aims to assess the perception of sustainable investments in a coastal area located in Tuscany, through the administration of a questionnaire among 750 people, including both tourists and house owners. The study adopted statistical logit and probit models to detect the perception of sustainable initiatives in relation to beach satisfaction. Moreover, this research developed a model for understanding if there are substantial differences in perception between Italian and foreign beach users and at the same time between residents/house owners and tourists. The findings reveal that those who perceive investments in sustainability are more than satisfied with beach and facilities. The model shows that foreigners and residents/house owners perceive sustainable investments implemented in the destination more than tourists and Italian respondents. This research can provide support to local operators and policymakers in defining the destination image in relation to sustainability.

Probit or Logit? Which is the better model to predict the longevity of seeds?

The prediction of seed longevity (P50) is traditionally performed by the use of the Probit model. However, due to the fact that the survival data are of binary origin (0,1), the fit of the model can be compromised by the non-normality of the residues. Consequently, this leads to prediction losses, despite the data being partially smoothed by Probit and Logit models. A possibility to reduce the effect of non-normality of the data would be to apply the principles of the central limit theorem, which states that non-normal residues tend to be normal as the n sample is increased. The Logit and Probit models differ in their normal and logistic distribution. Therefore, we developed a new estimation procedure by using a small increase of the n sample and tested it in the Probit and Logit functions to improve the prediction of P50. The results showed that the calculation of P50 by increasing the n samples from 4 to 6 replicates improved the index of correctness of the prediction. The Logit model presented better performance when compared with the Probit model, indicating that the estimation of P50 is more adequate when the adjustment of the data is performed by the Logit function.

Regression Analysis of Ordinal Logit and Probit Models to Predict the Factors Affecting Low Birth Weight

Low birth weight (LBW) has greater risk for experiencing problems. Based on Indonesian DHS data in 2012, the province with the highest infant mortality rate estimate was West Papua amounting to 75 per 1,000 live births. This study used logit and probit regression models to analyze the factors that caused low birth weight. It is thought that by comparing both logit and probit models, the best results could be obtained. The results of research showed that the independent variables that affected babies with LBW were the distance of pregnancy and maternal parity. If the distance of pregnancy was less than 2 years, it would increase the incidence of LBW by 2.7 times (p: 0,00: CI 1b: -4,05;CI ub: -1,50). Moreover, the distance of pregnancy which was less than 2 years would only improve LBW by 19.4 percent, compared with the distance of the pregnancy that was more than 2 years which would increase infant weight by 80.6 percent. As with maternal parity between 0 and more than 4, there was a chance of increasing the incidence of LBW by 1.94 times (p: 0,00; CI 1b: -2,66;CI ub: -1,21). On the other hand, maternal parity of 0 and parity > 4 would improve LBW by 74.2 percent, and a parity of 1 to 4 would only see 25.8 percent improvement. The result of this study suggested that there should be improvement in health promotions, such as family planning cuonseling and consultation for eligible couples.