Knowledge Flows and Networks: the Interplay between Local and Global Linkages within Bangalore IT Cluster

This doctoral work gains deeper insight into the dynamics of knowledge flows within and across clusters, unfolding their features, directions and strategic implications. Alliances, networks and personnel mobility are acknowledged as the three main channels of inter-firm knowledge flows, thus offering three heterogeneous measures to analyze the phenomenon. The interplay between the three channels and the richness of available research methods, has allowed for the elaboration of three different papers and perspectives. The common empirical setting is the IT cluster in Bangalore, for its distinguished features as a high-tech cluster and for its steady yearly two-digit growth around the service-based business model. The first paper deploys both a firm-level and a tie-level analysis, exploring the cases of 4 domestic companies and of 2 MNCs active the cluster, according to a cluster-based perspective. The distinction between business-domain knowledge and technical knowledge emerges from the qualitative evidence, further confirmed by quantitative analyses at tie-level. At firm-level, the specialization degree seems to be influencing the kind of knowledge shared, while at tie-level both the frequency of interaction and the governance mode prove to determine differences in the distribution of knowledge flows. The second paper zooms out and considers the inter-firm networks; particularly focusing on the role of cluster boundary, internal and external networks are analyzed, in their size, long-term orientation and exploration degree. The research method is purely qualitative and allows for the observation of the evolving strategic role of internal network: from exploitation-based to exploration-based. Moreover, a causal pattern is emphasized, linking the evolution and features of the external network to the evolution and features of internal network. The final paper addresses the softer and more micro-level side of knowledge flows: personnel mobility. A social capital perspective is here developed, which considers both employees’ acquisition and employees’ loss as building inter-firm ties, thus enhancing company’s overall social capital. Negative binomial regression analyses at dyad-level test the significant impact of cluster affiliation (cluster firms vs non-cluster firms), industry affiliation (IT firms vs non-IT fims) and foreign affiliation (MNCs vs domestic firms) in shaping the uneven distribution of personnel mobility, and thus of knowledge flows, among companies.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Sviluppo economico e qualità istituzionale: il ruolo di disuguaglianza e corruzione

Nell'ambito delle teorie dello sviluppo, un filone di studi, originato dai lavori di North (1973) e consolidatosi negli ultimi anni, individua nelle istituzioni, definite come le regole del gioco o i vincoli disegnati dagli uomini per disciplinare i loro rapporti, i fattori fondamentali dello sviluppo economico. Le istituzioni, nel modello elaborato da Acemoglu, Johnson e Robinson (2004), sono il frutto di interazioni dinamiche tra potere politico de jure, determinato dalle istituzioni politiche, e potere politico de facto, determinato dalla distribuzione delle risorse economiche. Sulla base di questa prospettiva teorica, questa tesi propone uno studio di carattere quantitativo sulla qualità istituzionale, la traduzione operativa del concetto di istituzioni, composta dalle tre fondamentali dimensioni di democrazia, efficienza ed efficacia del governo e assenza di corruzione. La prima parte, che analizza sistematicamente pro e contro di ciascuna tipologia di indicatori, è dedicata alla revisione delle misure quantitative di qualità istituzionale, e individua nei Worldwide Governance Indicators la misura più solida e consistente. Questi indici sono quindi utilizzati nella seconda parte, dove si propone un'analisi empirica sulle determinanti della qualità istituzionale. Le stime del modello di regressione cross-country evidenziano che la qualità istituzionale è influenzata da alcuni fattori prevalentemente esogeni come la geografia, la disponibilità di risorse naturali e altre caratteristiche storiche e culturali, insieme ad altri fattori di carattere più endogeno. In quest'ultima categoria, i risultati evidenziano un effetto positivo del livello di sviluppo economico, mentre la disuguaglianza economica mostra un impatto negativo su ciascuna delle tre dimensioni di qualità istituzionale, in particolare sulla corruzione. Questi risultati supportano la prospettiva teorica e suggeriscono che azioni di policy orientate alla riduzione delle disparità sono capaci di generare sviluppo rafforzando la democrazia, migliorando l'efficienza complessiva del sistema economico e riducendo i livelli di corruzione.