StudiesWorking Papers 
Scientific papers and internal presentations of master’s degree dissertations and PhD thesis by experts of Statistics Portugal.
All that glitters is not gold — [presentation], Pedro Cunha, Sónia Quaresma, Jorge Magalhães, Quality in Official Statistics 2016, May 2016


During the last census operation, Portugal performed a housing census, integrating geospatial information which constituted our initial National Households Register (FNA). Updating FNA is the next and critical stage to guarantee the enhancement of the data quality. Achieving this goal is only possible through the use of relevant information, with quality and contemporary data sources.
The best way to accomplish this purpose is using Statistic Portugal Data Warehouse to reuse the information and optimize the resources.

Functional Architecture of the Statistical Data Warehouse — [paper], Sónia Quaresma, Newport CoE DWH, April 2015
Parameter Estimation on Sensitive Questions in the Presence of Auxiliary Information — [presentation], Rita Sousa, Teses & Hipóteses, Lisboa: INE, May 2014 (only available in portuguese)
Methodological Study on Migration Statistics within the CPLP Countries — [paper], Conceição Veiga, Lisboa: INE, April 2014 (only available in portuguese)


The Methodological Study on Migration Statistics, in the framework of the eight countries of the Community of Portuguese-speaking Countries (CPLP), aims to describe and compare the production systems, the availability of data and methodologies in the area of statistics on migration. This study also intends to contribute to increasing cooperation between National Statistical Institutes (NSI), in exchanging information, procedures and technical knowledge supporting the development of migration statistics in the CPLP member countries: Angola, Brazil, Cape Verde, Guinea-Bissau, Mozambique, Portugal, Sao Tome and Principe and Timor-Leste.

Using Different Administrative Data Sources to Develop House Price Indexes for Portugal — [paper], Rui Evangelista, Ângelo Teixeira, OECD Workshop on House Price Statistics, Paris, 24-25 March 2014


The most recent economic and financial crises highlighted the lack of important information to monitor the performance of the housing market, whose imbalances could, through wealth and other effects, impact significantly on economic growth. This gap has prompted statistical institutes across Europe to develop strategies to improve the already existing house price statistics. This paper presents the work and experience of Statistics Portugal in this area, which involved the analysis of prices information taken at different stages of the buying and selling process and supported the compilation of appraisals-based and transactions-based house price indexes.

Poverty, Richness, and Inequality: Evidence for Portugal Using a Housing Comfort Index — [paper], Cristina Fernandes, Nuno Crespo, Nádia Simões, MPRA, Munich Personal RePEc Archive, December 2013


With data for Portugal we propose an index of housing comfort based on the Household Budget Survey. This index covers housing and durable goods grouped in two dimensions: basic comfort and complementary comfort. Taking this index as starting point we make two contributions. First we quantify the phenomena of poverty, richness, and inequality in housing comfort. Second, using an ordered probit model, we evaluate the determinants of housing comfort in Portugal. The results show significant rates of poverty (12.41%) and richness (22.03%). The evidence sustains that the differences between households derive mainly from complementary comfort and to a lesser extent from basic comfort items. Inequality in housing comfort, measured by the Gini coefficient, stands at 0.1263. The econometric study reveals that the region of residence of the household and the educational level and labor market state of the household reference person are among the most critical determinant factors of housing comfort.

Impacts of Education on Poverty and Material Deprivation of Households in Portugal, 2010 — [presentation], Susana Neves, Teses & Hipóteses Lisboa: INE, April 2013 (only available in portuguese)
The technology-based SME in the transition for a new energetic system in Portugal: Characteristics, Strategies and Barriers — [dissertation], Eduardo Pedroso, ISCTE Business School, Lisbon, October 2012 (only available in portuguese)


The co-evolution of technology and institutions creates stable systems that, despite meeting society’s needs, can create systemic barriers to the development and dissemination of alternative and more efficient technologies. This is currently the case for many energy, transportation and industrial technologies that are too dependent on the usage of fossil fuels and are the basis of many of today's environmental challenges. Therefore, the existence of a carbon lock-in requires major changes of existing technological systems towards a low-carbon economy, which depends on multiple agents, namely on New Technology-based Firms (NTBF) operating in the renewable energy sector.
This dissertation seeks to contribute to a better understanding of the strategies and barriers of such firms operating in the national context. For this purpose, a sample of SMEs located in the districts of Lisbon and Setúbal was analyzed. The firms were characterized according to their formation year, origin, number of employees, turnover, technological domain(s) and type of business. Then, through the conduction of interviews, seven case studies were carried out – six SMEs and one large firm.
The results reflect the behavioral heterogeneity of the firms analyzed but it is possible to highlight some dominant traits: they operate mostly in niches; present high technological and innovative dynamics; have highly skilled human resources; have well defined internationalization and expansion strategies; and face a set of barriers strongly associated with the phenomenon of carbon lock-in that, contrarily to what the theory predicted, is not focused on the issue of the cost-advantage of conventional technologies, but rather on the problematic configuration and evolution of public policies aiming to promote the development of a renewable energy sector.

When do you Hear the Warning Bells? — [paper], Pedro Cunha, Sónia Quaresma, Jorge Magalhães, Q2012, Athens, May 2012


Quality information can make the difference between good and on time decision making and support, and poor or delayed results. In order to increase data coherence, a strategic data warehouse has been built by Statistics Portugal in the last decade. Several challenges were faced not only on methodological issues but also concerning data owner and stewardship, management and generally promoting the reuse of already collected information. All these steps improved our data quality and got the warning bells ringing whenever there is a sign that there may be a problem. But sometimes the alert did not arrive soon enough and we needed to put in place an early warning system. Due to the data warehouse exploration, a lot of expertise on business intelligence was acquired and so Statistics Portugal decided to take a step further and use the capabilities and in-house know-how to follow the data collection surveys since their first moment - the field work. Promoting data quality from the beginning of the collection process was our challenge for the last couple of years and we now propose to share the experience we accumulated during this process.

Statistical Information supported by Business Intelligence — [paper], Sónia Quaresma, Lisboa: INE, May 2010 (only available in portuguese)
To Puzzle Out — [paper], Sónia Quaresma, ISI, Lisbon, August 2007


Since the beginning of times we’ve been trying to comprehend our reality, making sense of what happens and gathering information about it. Understanding our environment gives us the power to change it, adjust it or just to act in accord with its latest development. In a complex and ever-changing world multiple aspects have to be accounted for, demographics and finance, environment and agriculture, economics and research… National Statistical Institutes pay attention to all these areas, gathering information about each and every one of them.

To apprehend the reality is our aspiration at National Statistical Institutes and to do it we use every possible tool at our disposal. The aim of this paper is to present one of the most innovative tools in NSIs the Data Warehouses. We’ll talk about the evolution in data manipulation made possible by the technological advances in data collection which resulted in an increasing demand for more powerful ways to deal with the data, thus making DWs necessary.

Analysing DWs’ strengths in the business world, we’ll make clear their advantages for NSIs. Beyond that we shall see why they’re so well adjusted for an NSIs’ common needs of data dissemination and derived statistics production.

Even if DWs were not specially developed with statistical objectives, NSIs’ purpose, when data is collected is not only to gather information but furthermore to build Knowledge about the world. In order to do that, we have to be able to relate information to one another. Linking information from different areas we’ll give us different perspectives on the problems and an extraordinary new insight. And that’s precisely what data warehouses do, so that we can slowly begin to puzzle out our world!

Easy Does it! — [paper], Sónia Quaresma, Q2006 – European Conference on Quality in Official Statistics, Cardiff, May 2006


When preparing information for a data warehouse, namely integrating administrative and survey data, we must perform major transformations and a thorough revision of the data structure before we can store it in the database; hence the data warehouse design importance. In this design not only the structure should be accounted for but also the transformations needed and the way all concepts relate to one another. Just as an architect needs a building model to initiate construction, for a data warehouse a conceptual model has to be developed before data can be accommodated in the databases. This is the only way to ensure it will in the end serve our purposes and provide all the required results. Understanding this pressing issue we, at the Portuguese NSI, embarked in a project with the objective of establishing a data warehouse designing process.

We identified the major structures that should be present in a data warehouse model, and at the same time the most common elements in statistical dissemination. Several conceptual modeling proposals, found in the data warehouse design literature, were evaluated and the most promising was selected for testing. The computer science and statisticians teams worked together over the model, using real statistical domains of the Portuguese NSI to test its capabilities, which caused some characteristics of the modeling process to emerge.

A Brave New World — [paper], Sónia Quaresma, Q2004 – European Conference on Quality in Official Statistics, Mainz, May 2004


Every time an NSI launches a new survey, several services have to be prepared to deal with it. In particular its databases must be able to accommodate the incoming data. Currently, we use very large databases called Data Warehouses to store this information. The value of the data warehouses is their ability to support business intelligence. These specialized analytical databases typically provide support for complex multidimensional calculations and data aggregations, and are able to perform them in an acceptable amount of time. The data warehouses’ capabilities for data dissemination is regarded as an important contribution to quality. However, as we will show, data warehouses can and should be making greater contributions for the overall quality in statistical institutes. It’s through the process we will explain in this paper that simple data shall be transformed into meaningful information, comparable not only across the dimensions of its own project, but also with transverse variables whose source could be distinct surveys. When integrating information, sometimes we have to recover old information, which is difficult, and we may have to work with different classifications, trying to build bridges between projects and helping people to compromise. Each case is unique!

It is a hard process for all the people involved but it is worth the effort, because this is the approach that will lead us to a new perception of reality, and will ultimately help us build our brave new world.

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CSE AELA SICAE SEE - Sistema Estatico Europeu ESS Vision 2020   UE - Fundo Europeu de Desenvolvimento Regional POCI Compete 2020 Portugal 2020