Firms survival and international trade: The impact of exports and imports

Double Degree. A Work Project presented as part of the requirements for the Award of a Masters in Management from Nova School of Business and Economics and Maastricht University.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

Numerical simulation of blast effects on fibre grout RC panels

The main purpose of the present dissertation is the simulation of the response of fibre grout strengthened RC panels when subjected to blast effects using the Applied Element Method, in order to validate and verify its applicability. Therefore, four experimental models, three of which were strengthened with a cement-based grout, each reinforced by one type of steel reinforcement, were tested against blast effects. After the calibration of the experimental set-up, it was possible to obtain and compare the response to the blast effects of the model without strengthening (reference model), and a fibre grout strengthened RC panel (strengthened model). Afterwards, a numerical model of the reference model was created in the commercial software Extreme Loading for Structures, which is based on the Applied Element Method, and calibrated to the obtained experimental results, namely to the residual displacement obtained by the experimental monitoring system. With the calibration verified, it is possible to assume that the numerical model correctly predicts the response of fibre grout RC panels when subjected to blast effects. In order to verify this assumption, the strengthened model was modelled and subjected to the blast effects of the corresponding experimental set-up. The comparison between the residual and maximum displacements and the bottom surface’s cracking obtained in the experimental and the numerical tests yields a difference of 4 % for the maximum displacements of the reference model, and a difference of 4 and 10 % for the residual and maximum displacements of the strengthened model, respectively. Additionally, the cracking on the bottom surface of the models was similar in both methods. Therefore, one can conclude that the Applied ElementMethod can correctly predict and simulate the response of fibre grout strengthened RC panels when subjected to blast effects.

Column-based databases: estudo exploratório no âmbito das bases de dados NoSQL

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Document-based databases: estudo comparativo no âmbito das bases de dados NoSql

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

The electoral dynamics of human development

This paper analyses the impact of elections on the dynamics of human development in a panel of 82 countries over the period 1980-2013. The incidence of partisan and political support effects is also taken into account. A GMM estimator is employed in the empirical analysis and the results point out to the presence of an electoral cycle in the growth rate of human development. Majority governments also influence it, but no clear evidence is found regarding partisan effects. The electoral cycles have proved to be stronger in non-OECD countries, in countries with less frequent elections, with lower levels of income and human development, in presidential and non-plurality systems and in proportional representation regimes. They have also become more intense in this millennium.

Interactions between fiscal and monetary policy

Mestrado em Economia Monetária e Financeira

Firm Size and Short-Term Dynamics in Aggregate Entry and Exit

Much of the research on industry dynamics focuses on the interdependence between the sectorial rates of entry and exit. This paper argues that the size of firms and the reaction-adjustment period are important conditions missed in this literature. I illustrate the effects of this omission using data from the Spanish manufacturing industries between 1994 and 2001. Estimates from systems of equations models provide evidence of a conical revolving door phenomenon and of partial adjustments in the replacement-displacement of large firms. KEYWORDS: aggregation, industry dynamics, panel data, symmetry, simultaneity. JEL CLASSIFICATION: C33, C52, L60, L11

The demand elasticity on tolled motorways

This paper analyses the elasticities of demand in tolled motorways in Spain with respect to the main variables influencing it. The demand equation is estimated using a panel data set where the cross-section observations correspond to the different Spanish tolled motorways sections, and the temporal dimension ranges from the beginning of the eighties until the end of the nineties. The results show a high elasticity with respect to the economic activity level. The average elasticity with respect to petrol price falls around -0.3, while toll elasticities clearly vary across motorway sections. These motorway sections are classified into four groups according to the estimated toll elasticity with values that range from -0.21 for the most inelastic to -0.83 for the most elastic. The main factors that explain such differences are the quality of the alternative road and the length of the section. The long-term effect is about 50 per cent higher than the short term one; however, the period of adjustment is relatively short.

Locations and Relocations:Modelling, Determinants, and Interrelations

Empirical studies on industrial location do not typically distinguish between new and relocated establishments. This paper addresses this shortcoming using data on the frequency of these events in municipalities of the same economic-administrative region. This enables us to test not only for differences in their determinants but also for interrelations between start-ups and relocations. Estimates from count regression models for cross-section and panel data show that, although partial effects differ, common patterns arise in “institutional” and “neoclassical” explanatory factors. Also, start-ups and relocations are positive but asymmetrically related. JEL classification: C25, R30, R10. Keywords: cities, count data models, industrial location

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Immigration and Firm Growth: Evidence from Spanish cities

This article analyses the effect of immigration flows on the growth and efficiency of manufacturing firms in Spanish cities. To date, most studies have tended to focus on the effect immigrants have on labour markets at an aggregate level. Here, however, we undertake an exhaustive analysis at the firm level and report conclusive empirical findings. Ten years ago, Spain began to register massive immigration flows, concentrated above all on its most dynamic and advanced regions. Here, therefore, rather than focusing on the impact this has had on Spain’s labour market (changes to the skill structure of the workforce, increase in labour supply, the displacement of native workers, etc.), we examine the arrival of immigrants in terms of the changes this has meant to the structure of the country’s cities and their amenities. Thus, we argue that the impact of immigration on firm performance should not only be considered in terms of the labour market, but also in terms of how a city’s amenities can affect the performance of firms. Employing a panel data methodology, we show that the increasing pressure brought to bear by immigrants has a positive effect on the evolution of labour productivity and wages and a negative effect on the job evolution of these manufacturing firms. In addition, both small and new firms are more sensitive to the pressures of such immigrant inflows, while foreign market oriented firms report higher productivity levels and a less marked impact of immigration than their counterparts. In this paper, we also present a set of instruments to correct the endogeneity bias, which confirms the effect of local immigration flows on the performance of manufacturing firms.

Deconstructing Shocks and Persistence in OECD Real Exchange Rates

This paper analyzes the persistence of shocks that affect the real exchange rates for a panel of seventeen OECD developed countries during the post-Bretton Woods era. The adoption of a panel data framework allows us to distinguish two different sources of shocks, i.e. the idiosyncratic and the common shocks, each of which may have di¤erent persistence patterns on the real exchange rates. We first investigate the stochastic properties of the panel data set using panel stationarity tests that simultaneously consider both the presence of cross-section dependence and multiple structural breaks that have not received much attention in previous persistence analyses. Empirical results indicate that real exchange rates are non-stationary when the analysis does not account for structural breaks, although this conclusion is reversed when they are modeled. Consequently, misspecification errors due to the non-consideration of structural breaks leads to upward biased shocks' persistence measures. The persistence measures for the idiosyncratic and common shocks have been estimated in this paper always turn out to be less than one year.

The causal relationship between Individual’s choice behavior and self-reported satisfaction: the case of residential mobility in the EU

One of the most persistent and lasting debates in economic research refers to whether the answers to subjective questions can be used to explain individuals’ economic behavior. Using panel data for twelve EU countries, in the present study we analyze the causal relationship between self-reported housing satisfaction and residential mobility. Our results indicate that: i) households unsatisfied with their current housing situation are more likely to move; ii) housing satisfaction raises after a move, and; iii) housing satisfaction increases with the transition from being a renter to becoming a homeowner. Some interesting cross-country differences are observed. Our findings provide evidence in favor of use of subjective indicators of satisfaction with certain life domains in the analysis of individuals’ economic conduct.

Export-market dynamics and the probability of firm closure: Evidence for the UK

This study presents the first empirical analysis of the determinants of firm closure in the UK with an emphasis on the role of export-market dynamics, using panel data for a nationally representative group of firms operating in all-market based sectors during 1997-2003. Our findings show that the probability of closure is (cet. par.) significantly lower for exporters, particularly those experiencing export-market entry and exit. Having controlled for other attributes associated with productivity (such as size and export status), the following factors are found to increase the firm’s survival prospects: higher capital intensity and TFP, foreign ownership, young age, displacement effects (through relatively high rates of entry of firms in each industry), and belonging to certain industries. Interestingly, increased import penetration (a proxy for lower trade costs) leads to a lower hazard rate for exporting entrants and continuous exporters, whilst inducing a higher hazard rate for domestic producers or those that quit exporting.