Procedures of quality control and data analysis of multi-site ground-based observations for the absolute flux calibration of Gaia

The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

Development of new tools and devices for CMB and foreground data analysis and future experiments

The discovery of the Cosmic Microwave Background (CMB) radiation in 1965 is one of the fundamental milestones supporting the Big Bang theory. The CMB is one of the most important source of information in cosmology. The excellent accuracy of the recent CMB data of WMAP and Planck satellites confirmed the validity of the standard cosmological model and set a new challenge for the data analysis processes and their interpretation. In this thesis we deal with several aspects and useful tools of the data analysis. We focus on their optimization in order to have a complete exploitation of the Planck data and contribute to the final published results. The issues investigated are: the change of coordinates of CMB maps using the HEALPix package, the problem of the aliasing effect in the generation of low resolution maps, the comparison of the Angular Power Spectrum (APS) extraction performances of the optimal QML method, implemented in the code called BolPol, and the pseudo-Cl method, implemented in Cromaster. The QML method has been then applied to the Planck data at large angular scales to extract the CMB APS. The same method has been applied also to analyze the TT parity and the Low Variance anomalies in the Planck maps, showing a consistent deviation from the standard cosmological model, the possible origins for this results have been discussed. The Cromaster code instead has been applied to the 408 MHz and 1.42 GHz surveys focusing on the analysis of the APS of selected regions of the synchrotron emission. The new generation of CMB experiments will be dedicated to polarization measurements, for which are necessary high accuracy devices for separating the polarizations. Here a new technology, called Photonic Crystals, is exploited to develop a new polarization splitter device and its performances are compared to the devices used nowadays.

Early Warning For Large Earthquakes: Observations, Models and Real-Time Data Analysis

This thesis is a collection of works focused on the topic of Earthquake Early Warning, with a special attention to large magnitude events. The topic is addressed from different points of view and the structure of the thesis reflects the variety of the aspects which have been analyzed. The first part is dedicated to the giant, 2011 Tohoku-Oki earthquake. The main features of the rupture process are first discussed. The earthquake is then used as a case study to test the feasibility Early Warning methodologies for very large events. Limitations of the standard approaches for large events arise in this chapter. The difficulties are related to the real-time magnitude estimate from the first few seconds of recorded signal. An evolutionary strategy for the real-time magnitude estimate is proposed and applied to the single Tohoku-Oki earthquake. In the second part of the thesis a larger number of earthquakes is analyzed, including small, moderate and large events. Starting from the measurement of two Early Warning parameters, the behavior of small and large earthquakes in the initial portion of recorded signals is investigated. The aim is to understand whether small and large earthquakes can be distinguished from the initial stage of their rupture process. A physical model and a plausible interpretation to justify the observations are proposed. The third part of the thesis is focused on practical, real-time approaches for the rapid identification of the potentially damaged zone during a seismic event. Two different approaches for the rapid prediction of the damage area are proposed and tested. The first one is a threshold-based method which uses traditional seismic data. Then an innovative approach using continuous, GPS data is explored. Both strategies improve the prediction of large scale effects of strong earthquakes.

Data management and data analysis in the large European projects GEHA (GEnetics of Healthy Aging) and NU-AGE (NUtrition and AGEing): a bioinformatic approach

The aging process is characterized by the progressive fitness decline experienced at all the levels of physiological organization, from single molecules up to the whole organism. Studies confirmed inflammaging, a chronic low-level inflammation, as a deeply intertwined partner of the aging process, which may provide the “common soil” upon which age-related diseases develop and flourish. Thus, albeit inflammation per se represents a physiological process, it can rapidly become detrimental if it goes out of control causing an excess of local and systemic inflammatory response, a striking risk factor for the elderly population. Developing interventions to counteract the establishment of this state is thus a top priority. Diet, among other factors, represents a good candidate to regulate inflammation. Building on top of this consideration, the EU project NU-AGE is now trying to assess if a Mediterranean diet, fortified for the elderly population needs, may help in modulating inflammaging. To do so, NU-AGE enrolled a total of 1250 subjects, half of which followed a 1-year long diet, and characterized them by mean of the most advanced –omics and non –omics analyses. The aim of this thesis was the development of a solid data management pipeline able to efficiently cope with the results of these assays, which are now flowing inside a centralized database, ready to be used to test the most disparate scientific hypotheses. At the same time, the work hereby described encompasses the data analysis of the GEHA project, which was focused on identifying the genetic determinants of longevity, with a particular focus on developing and applying a method for detecting epistatic interactions in human mtDNA. Eventually, in an effort to propel the adoption of NGS technologies in everyday pipeline, we developed a NGS variant calling pipeline devoted to solve all the sequencing-related issues of the mtDNA.

Essays on the Empirical Analysis of Economic and Political Development in Sub-Saharan Africa

In Sub-Saharan Africa, non-democratic events, like civil wars and coup d'etat, destroy economic development. This study investigates both domestic and spatial effects on the likelihood of civil wars and coup d'etat. To civil wars, an increase of income growth is one of common research conclusions to stop wars. This study adds a concern on ethnic fractionalization. IV-2SLS is applied to overcome causality problem. The findings document that income growth is significant to reduce number and degree of violence in high ethnic fractionalized countries, otherwise they are trade-off. Income growth reduces amount of wars, but increases its violent level, in the countries with few large ethnic groups. Promoting growth should consider ethnic composition. This study also investigates the clustering and contagion of civil wars using spatial panel data models. Onset, incidence and end of civil conflicts spread across the network of neighboring countries while peace, the end of conflicts, diffuse only with the nearest neighbor. There is an evidence of indirect links from neighboring income growth, without too much inequality, to reduce the likelihood of civil wars. To coup d'etat, this study revisits its diffusion for both all types of coups and only successful ones. The results find an existence of both domestic and spatial determinants in different periods. Domestic income growth plays major role to reduce the likelihood of coup before cold war ends, while spatial effects do negative afterward. Results on probability to succeed coup are similar. After cold war ends, international organisations seriously promote democracy with pressure against coup d'etat, and it seems to be effective. In sum, this study indicates the role of domestic ethnic fractionalization and the spread of neighboring effects to the likelihood of non-democratic events in a country. Policy implementation should concern these factors.

The firm. Techno-organizational changes, industrial relations and performances. An enquiry on Reggio Emilia local industrial system

It is not unknown that the evolution of firm theories has been developed along a path paved by an increasing awareness of the organizational structure importance. From the early “neoclassical” conceptualizations that intended the firm as a rational actor whose aim is to produce that amount of output, given the inputs at its disposal and in accordance to technological or environmental constraints, which maximizes the revenue (see Boulding, 1942 for a past mid century state of the art discussion) to the knowledge based theory of the firm (Nonaka & Takeuchi, 1995; Nonaka & Toyama, 2005), which recognizes in the firm a knnowledge creating entity, with specific organizational capabilities (Teece, 1996; Teece & Pisano, 1998) that allow to sustaine competitive advantages. Tracing back a map of the theory of the firm evolution, taking into account the several perspectives adopted in the history of thought, would take the length of many books. Because of that a more fruitful strategy is circumscribing the focus of the description of the literature evolution to one flow connected to a crucial question about the nature of firm’s behaviour and about the determinants of competitive advantages. In so doing I adopt a perspective that allows me to consider the organizational structure of the firm as an element according to which the different theories can be discriminated. The approach adopted starts by considering the drawbacks of the standard neoclassical theory of the firm. Discussing the most influential theoretical approaches I end up with a close examination of the knowledge based perspective of the firm. Within this perspective the firm is considered as a knowledge creating entity that produce and mange knowledge (Nonaka, Toyama, & Nagata, 2000; Nonaka & Toyama, 2005). In a knowledge intensive organization, knowledge is clearly embedded for the most part in the human capital of the individuals that compose such an organization. In a knowledge based organization, the management, in order to cope with knowledge intensive productions, ought to develop and accumulate capabilities that shape the organizational forms in a way that relies on “cross-functional processes, extensive delayering and empowerment” (Foss 2005, p.12). This mechanism contributes to determine the absorptive capacity of the firm towards specific technologies and, in so doing, it also shape the technological trajectories along which the firm moves. After having recognized the growing importance of the firm’s organizational structure in the theoretical literature concerning the firm theory, the subsequent point of the analysis is that of providing an overview of the changes that have been occurred at micro level to the firm’s organization of production. The economic actors have to deal with challenges posed by processes of internationalisation and globalization, increased and increasing competitive pressure of less developed countries on low value added production activities, changes in technologies and increased environmental turbulence and volatility. As a consequence, it has been widely recognized that the main organizational models of production that fitted well in the 20th century are now partially inadequate and processes aiming to reorganize production activities have been widespread across several economies in recent years. Recently, the emergence of a “new” form of production organization has been proposed both by scholars, practitioners and institutions: the most prominent characteristic of such a model is its recognition of the importance of employees commitment and involvement. As a consequence it is characterized by a strong accent on the human resource management and on those practices that aim to widen the autonomy and responsibility of the workers as well as increasing their commitment to the organization (Osterman, 1994; 2000; Lynch, 2007). This “model” of production organization is by many defined as High Performance Work System (HPWS). Despite the increasing diffusion of workplace practices that may be inscribed within the concept of HPWS in western countries’ companies, it is an hazard, to some extent, to speak about the emergence of a “new organizational paradigm”. The discussion about organizational changes and the diffusion of HPWP the focus cannot abstract from a discussion about the industrial relations systems, with a particular accent on the employment relationships, because of their relevance, in the same way as production organization, in determining two major outcomes of the firm: innovation and economic performances. The argument is treated starting from the issue of the Social Dialogue at macro level, both in an European perspective and Italian perspective. The model of interaction between the social parties has repercussions, at micro level, on the employment relationships, that is to say on the relations between union delegates and management or workers and management. Finding economic and social policies capable of sustaining growth and employment within a knowledge based scenario is likely to constitute the major challenge for the next generation of social pacts, which are the main social dialogue outcomes. As Acocella and Leoni (2007) put forward the social pacts may constitute an instrument to trade wage moderation for high intensity in ICT, organizational and human capital investments. Empirical evidence, especially focused on the micro level, about the positive relation between economic growth and new organizational designs coupled with ICT adoption and non adversarial industrial relations is growing. Partnership among social parties may become an instrument to enhance firm competitiveness. The outcome of the discussion is the integration of organizational changes and industrial relations elements within a unified framework: the HPWS. Such a choice may help in disentangling the potential existence of complementarities between these two aspects of the firm internal structure on economic and innovative performance. With the third chapter starts the more original part of the thesis. The data utilized in order to disentangle the relations between HPWS practices, innovation and economic performance refer to the manufacturing firms of the Reggio Emilia province with more than 50 employees. The data have been collected through face to face interviews both to management (199 respondents) and to union representatives (181 respondents). Coupled with the cross section datasets a further data source is constituted by longitudinal balance sheets (1994-2004). Collecting reliable data that in turn provide reliable results needs always a great effort to which are connected uncertain results. Data at micro level are often subjected to a trade off: the wider is the geographical context to which the population surveyed belong the lesser is the amount of information usually collected (low level of resolution); the narrower is the focus on specific geographical context, the higher is the amount of information usually collected (high level of resolution). For the Italian case the evidence about the diffusion of HPWP and their effects on firm performances is still scanty and usually limited to local level studies (Cristini, et al., 2003). The thesis is also devoted to the deepening of an argument of particular interest: the existence of complementarities between the HPWS practices. It has been widely shown by empirical evidence that when HPWP are adopted in bundles they are more likely to impact on firm’s performances than when adopted in isolation (Ichniowski, Prennushi, Shaw, 1997). Is it true also for the local production system of Reggio Emilia? The empirical analysis has the precise aim of providing evidence on the relations between the HPWS dimensions and the innovative and economic performances of the firm. As far as the first line of analysis is concerned it must to be stressed the fundamental role that innovation plays in the economy (Geroski & Machin, 1993; Stoneman & Kwoon 1994, 1996; OECD, 2005; EC, 2002). On this point the evidence goes from the traditional innovations, usually approximated by R&D investment expenditure or number of patents, to the introduction and adoption of ICT, in the recent years (Brynjolfsson & Hitt, 2000). If innovation is important then it is critical to analyse its determinants. In this work it is hypothesised that organizational changes and firm level industrial relations/employment relations aspects that can be put under the heading of HPWS, influence the propensity to innovate in product, process and quality of the firm. The general argument may goes as follow: changes in production management and work organization reconfigure the absorptive capacity of the firm towards specific technologies and, in so doing, they shape the technological trajectories along which the firm moves; cooperative industrial relations may lead to smother adoption of innovations, because not contrasted by unions. From the first empirical chapter emerges that the different types of innovations seem to respond in different ways to the HPWS variables. The underlying processes of product, process and quality innovations are likely to answer to different firm’s strategies and needs. Nevertheless, it is possible to extract some general results in terms of the most influencing HPWS factors on innovative performance. The main three aspects are training coverage, employees involvement and the diffusion of bonuses. These variables show persistent and significant relations with all the three innovation types. The same do the components having such variables at their inside. In sum the aspects of the HPWS influence the propensity to innovate of the firm. At the same time, emerges a quite neat (although not always strong) evidence of complementarities presence between HPWS practices. In terns of the complementarity issue it can be said that some specific complementarities exist. Training activities, when adopted and managed in bundles, are related to the propensity to innovate. Having a sound skill base may be an element that enhances the firm’s capacity to innovate. It may enhance both the capacity to absorbe exogenous innovation and the capacity to endogenously develop innovations. The presence and diffusion of bonuses and the employees involvement also spur innovative propensity. The former because of their incentive nature and the latter because direct workers participation may increase workers commitment to the organizationa and thus their willingness to support and suggest inovations. The other line of analysis provides results on the relation between HPWS and economic performances of the firm. There have been a bulk of international empirical studies on the relation between organizational changes and economic performance (Black & Lynch 2001; Zwick 2004; Janod & Saint-Martin 2004; Huselid 1995; Huselid & Becker 1996; Cappelli & Neumark 2001), while the works aiming to capture the relations between economic performance and unions or industrial relations aspects are quite scant (Addison & Belfield, 2001; Pencavel, 2003; Machin & Stewart, 1990; Addison, 2005). In the empirical analysis the integration of the two main areas of the HPWS represent a scarcely exploited approach in the panorama of both national and international empirical studies. As remarked by Addison “although most analysis of workers representation and employee involvement/high performance work practices have been conducted in isolation – while sometimes including the other as controls – research is beginning to consider their interactions” (Addison, 2005, p.407). The analysis conducted exploiting temporal lags between dependent and covariates, possibility given by the merger of cross section and panel data, provides evidence in favour of the existence of HPWS practices impact on firm’s economic performance, differently measured. Although it does not seem to emerge robust evidence on the existence of complementarities among HPWS aspects on performances there is evidence of a general positive influence of the single practices. The results are quite sensible to the time lags, inducing to hypothesize that time varying heterogeneity is an important factor in determining the impact of organizational changes on economic performance. The implications of the analysis can be of help both to management and local level policy makers. Although the results are not simply extendible to other local production systems it may be argued that for contexts similar to the Reggio Emilia province, characterized by the presence of small and medium enterprises organized in districts and by a deep rooted unionism, with strong supporting institutions, the results and the implications here obtained can also fit well. However, a hope for future researches on the subject treated in the present work is that of collecting good quality information over wider geographical areas, possibly at national level, and repeated in time. Only in this way it is possible to solve the Gordian knot about the linkages between innovation, performance, high performance work practices and industrial relations.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Perceptual maps analysis for organic food consumers in China: a study on Shanghai consumers

Although in Europe and in the USA many studies focus on organic, little is known on the topic in China. This research provides an insight on Shanghai consumers’ perception of organic, aiming at understanding and representing in graphic form the network of mental associations that stems from the organic concept. To acquire, process and aggregate the individual networks it was used the “Brand concept mapping” methodology (Roedder et al., 2006), while the data analysis was carried out also using analytic procedures. The results achieved suggest that organic food is perceived as healthy, safe and costly. Although these attributes are pretty much consistent with the European perception, some relevant differences emerged. First, organic is not necessarily synonymous with natural product in China, also due to a poor translation of the term in the Chinese language that conveys the idea of a manufactured product. Secondly, the organic label has to deal with the competition with the green food label in terms of image and positioning on the market, since they are easily associated and often confused. “Environmental protection” also emerged as relevant association, while the ethical and social values were not mentioned. In conclusion, health care and security concerns are the factors that influence most the food consumption in China (many people are so concerned about food safety that they found it difficult to shop), and the associations “Safe”, “Pure and natural”, “without chemicals” and “healthy” have been identified as the best candidates for leveraging a sound image of organic food .

Pyrolysis-Gas Chromatography-Mass Spectometry and Chemometric Analysis for the Characterization of Complex Matrices

The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.

Patterns of regional differentiation in post-Soviet Russia

This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

Institutional Processes and Discursive Strategies: Rhetoric and Vocabulary Analysis of CSR and Sustainability

The candidate tackled an important issue in contemporary management: the role of CSR and Sustainability. The research proposal focused on a longitudinal and inductive research, directed to specify the evolution of CSR and contribute to the new institutional theory, in particular institutional work framework, and to the relation between institutions and discourse analysis. The documental analysis covers all the evolution of CSR, focusing also on a number of important networks and associations. Some of the methodologies employed in the thesis have been employed as a consequence of data analysis, in a truly inductive research process. The thesis is composed by two section. The first section mainly describes the research process and the analyses results. The candidates employed several research methods: a longitudinal content analysis of documents, a vocabulary research with statistical metrics as cluster analysis and factor analysis, a rhetorical analysis of justifications. The second section puts in relation the analysis results with theoretical frameworks and contributions. The candidate confronted with several frameworks: Actor-Network-Theory, Institutional work and Boundary Work, Institutional Logic. Chapters are focused on different issues: a historical reconstruction of CSR; a reflection about symbolic adoption of recurrent labels; two case studies of Italian networks, in order to confront institutional and boundary works; a theoretical model of institutional change based on contradiction and institutional complexity; the application of the model to CSR and Sustainability, proposing Sustainability as a possible institutional logic.

Modeling the spatial dynamics of economic models

The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.

Shareholder protection and stock market development

The dissertation contains five parts: An introduction, three major chapters, and a short conclusion. The First Chapter starts from a survey and discussion of the studies on corporate law and financial development literature. The commonly used methods in these cross-sectional analyses are biased as legal origins are no longer valid instruments. Hence, the model uncertainty becomes a salient problem. The Bayesian Model Averaging algorithm is applied to test the robustness of empirical results in Djankov et al. (2008). The analysis finds that their constructed legal index is not robustly correlated with most of the various stock market outcome variables. The second Chapter looks into the effects of minority shareholders protection in corporate governance regime on entrepreneurs' ex ante incentives to undertake IPO. Most of the current literature focuses on the beneficial part of minority shareholder protection on valuation, while overlooks its private costs on entrepreneur's control. As a result, the entrepreneur trade-offs the costs of monitoring with the benefits of cheap sources of finance when minority shareholder protection improves. The theoretical predictions are empirically tested using panel data and GMM-sys estimator. The third Chapter investigates the corporate law and corporate governance reform in China. The corporate law in China regards shareholder control as the means to the ends of pursuing the interests of stakeholders, which is inefficient. The Chapter combines the recent development of theories of the firm, i.e., the team production theory and the property rights theory, to solve such problem. The enlightened shareholder value, which emphasizes on the long term valuation of the firm, should be adopted as objectives of listed firms. In addition, a move from the mandatory division of power between shareholder meeting and board meeting to the default regime, is proposed.

Topics in Local Economic Development

This thesis contributes to the current debate in literature about local economic development by considering two different topics: quality of institutions, and the role of clusters in innovation and productivity growth. The research is built upon three papers. The first paper deals with the analysis of the effect of administrative continuity on administrative efficiency. The analysis underlines the importance of different typologies of social capital. Findings reveal a positive impact on administrative efficiency (AE) by administrative continuity (AC) when it is coupled by bridging and linking social capital. On the contrary, bonding social capital influences negatively the effect by AC on AE. The second paper investigates the spatial interaction in levels of quality of government (QoG) among European regions. Notwithstanding the largely recognised role by institutions in the design of regional policies, no study has been conducted about the mechanisms of interaction and diffusion of QoG at regional level. This research wants to overcome this knowledge gap in literature. Findings reveal a heterogeneity in spatial interaction among groups of regions, i.e. ‘leader regions’ (Northern regions) and ‘lagging regions’ (Southern regions), when considering different mechanisms of interaction (learning / imitating competition and pure competition). Moreover, the effect of wealth on the levels of QoG is nonlinear. Finally, the third paper analyses the relation among specialization and productivity within the agricultural sector. In literature, the study of clusters dynamics has long neglected agriculture. The analysis describes the changes in sectorial specialization for eight main crop groups in Italian regions (NUTS 3), assessing the existence of spatial autocorrelations by using an exploratory data analysis. Furthermore, the effect of specialization on productivity is analysed within the main crop groups using a spatial panel data model. Findings reveal a marked tendency to specialization in the Italian agriculture, and a heterogeneous effect by specialization on productivity.