A historical approach to the new secular stagnation hypothesis

In this paper, we analyze the behavior of real interest rates over the long-run using historical data for nine developed economies, to assess the extent to which the recent decline observed in most advanced countries is at odds with the past data, as suggested by the Secular Stagnation hypothesis. By using data from 1703 and performing stationarity and structural breaks tests, we find that the recent decline in interest rates is not explained by a structural break in the time series. Our results also show that considering long-run data leads to different conclusions than using short-run data.

How servant leadership is perceiver by leaders and followers in a Portuguese organizational context

Servant leadership theory has been the subject of great academic discussion, namely in what concerns reaching a consensus for its definition. As many frameworks have been designed in order to define the servant leader’s characteristics, we based ourselves in van Dierendonck’s review and synthesis on servant leadership (2011) to assess how it is perceived in a Portuguese organizational context. After performing several interviews in a private health care organization, we conclude that the perception of servant leadership is generally positive and that its characteristics seem to be in line with academic literature. However, some issues arose such as a seemingly lack of relevance given to authenticity and humility, the latter being a unique attribute of servant leadership. Also, we found a discrepancy between hierarchical levels’ perception of servant leadership characteristics as well as questioning if an over emphasis on service can diminish the servant leader’s impact on organizational performance.

Critical incident study on forgiveness in the organizational context

Forgiveness has been subject of interest, mainly in the psychology fields of study. Relatively to the organizational context, this topic has been somehow put aside and settled as something that is purely an intra-individual phenomenon which organizations cannot force, or even stimulate. As conflicts are common within organizations and being often difficult to overcome, eyes have turned into the role forgiveness might take in this scenario. Despite forgiveness being accepted as an intrapersonal decision and a result of predisposition as it is a result of education and culture. This study, as some already done, refuses to accept forgiveness as an unchangeable behavior that cannot be manipulated or induced by managers or by organizational context. Therefore, offering a set of incidents as well as their classification, that have been identified by individuals performing different types organizational roles in different organization which is believed as being a genuine way of delivering to the reader a set of actions and behaviors that if taken, may incentivize or inhibit forgiveness.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.