Mota-Engil new prospects of growth: Overcoming the financial crisis

The 2008 global financial crisis caused the collapse of business key sectors, declines in consumer wealth and a fall in economic activity resulting in a global recession. In some European countries, the 2008 crisis contributed to a sovereign-debt crisis which had a strong impact in Southern European countries. The construction sector was particularly affected, with budget cuts disturbing public investment and no financing available for private constructors. This report intends to explain how Mota-Engil, faced this situation of low growth, and which strategies were adopted by the management to overcome the difficult economic conjecture, mainly in its domestic market: Portugal. The report is organized as a case-study. The first part, the case narrative, is subdivided into 6 parts, and the second part is the teaching note. The teaching note is constituted by the four questions and their respective responses.

Buy, sell and chatter: A case analysis of a Lisbon flea market

This thesis aims explore the sociocultural as well as economic significance of the modern-day flea market, as a form of alternative marketplace system. More specifically, the main goal of the research is to determine the motivation for participation in flea markets of different participants, from vendors to consumers, using an interactionist perspective. By studying these groups in details, I seek to explore the embeddedness of social aspects in economic activity and vice versa. The basic assumption is to put aside the previous notions of the flea market as a second-order system with implied inferiority, and to explore the potential of the flea market to both challenge and complement more formal marketplace systems, by comparing and contrasting the flea market with market venues that belong to the formal sector. Feira da Ladra in Lisbon, Portugal, the oldest a hugely successful flea market in Europe, was chosen to be the research site, where its economic participants were studied in details in various exchanges, using naturalistic observations, semi-structured interviews and a sociocultural perspective.

Stops and bonanzas in the EU: Does being part of the Euro Area make a difference?

In this paper, we investigate whether being part of the euro area influences the conditional probability of going through a sudden stop or a bonanza of capital flows. Our sample period is from 1995 until 2014. We identify these two phenomena and we evaluate which push and pull factors help predict the conditional probability of experiencing one of them. We find that most countries had significant capital inflows until 2008 and that there were more sudden stops during the recent financial crisis than in any other moment in our sample. The factors that better help forecast the conditional probability of a sudden stop are global uncertainty (represented by the push factor “Volatility Index”), and the domestic economic activity (pull factors “GDP growth” and “consumer confidence”). An indicator of country risk (pull factor “change in credit rating”) is the most significant one for predicting bonanzas. Ultimately, we find no evidence that being part of the euro area influences the conditional probability of going through a sudden stop or a bonanza.

How to take advantage of wine tourism: Creation of a new concept for central Alentejo based on its potential and worldwide success factors

Wine Tourism is gaining importance in today’s world and more destinations and establishments have been arising. After understanding the importance of this economic activity and the factors it must have to succeed, a new project was conceived for Central Alentejo taking into account its potential. This project is an example of how to take advantage of Wine Tourism in wine regions that are underexplored, such as Aldeias de Montoito, the village near Redondo to which a Business Plan will be created, explaining the strategies to pursue in order to have a successful Wine Tourism destination.

Effects of quantitative easing on the USA economy: A test for policy effectiveness

The catastrophic disruption in the USA financial system in the wake of the financial crisis prompted the Federal Reserve to launch a Quantitative Easing (QE) programme in late 2008. In line with Pesaran and Smith (2014), I use a policy effectiveness test to assess whether this massive asset purchase programme was effective in stimulating the economic activity in the USA. Specifically, I employ an Autoregressive Distributed Lag Model (ARDL), in order to obtain a counterfactual for the USA real GDP growth rate. Using data from 1983Q1 to 2009Q4, the results show that the beneficial effects of QE appear to be weak and rather short-lived. The null hypothesis of policy ineffectiveness is not rejected, which suggests that QE did not have a meaningful impact on output growth.

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.