Determinants of cesarean delivery, a population-based study in the Emilia Romagna Region

Cesarean Delivery (CD) rates are rising in many parts of the world. In order to define strategies to reduce them, it is important to explore the role of clinical and organizational factors. This thesis has the objective to describe the contemporary CD practice and study clinical and organizational variables as determinants of CD in all women who gave birth between 2005 and June 2010 in the Emilia Romagna region (Italy). All hospital discharge abstracts of women who delivered between 2005 and mid 2010 in the region were selected and linked with birth certificates. In addition to descriptive statistics, in order to study the role of clinical and organizational variables (teaching or non-teaching hospital, birth volumes, time and day of delivery) multilevel Poisson regression models and a classification tree were used. A substantial inter-hospital variability in CD rate was found, and this was only partially explained by the considered variables. The most important risk factors of CD were: previous CD (RR 4,95; 95%CI: 4,85-5,05), cord prolapse (RR 3,51; 95% CI:2,96-4,16), and malposition/malpresentation (RR 2,72; 95%CI: 2,66-2,77). Delivery between 7 pm and 7 am and during non working days protect against CD in all subgroups including those with a small number of elective CDs while delivery at a teaching hospital and birth volumes were not statistically significant risk factors. The classification tree shows that previous CD and malposition/malpresentation are the most important variables discriminating between high and low risk of CD. These results indicate that other not considered factors might explain CD variability and do not provide clear evidence that small hospitals have a poor performance in terms of CD rate. Some strategies to reduce CD could be found by focusing on the differences in delivery practice between day and night and between working and no-working day deliveries.

Understanding Recent Developments in the Turkish Labor Market: Empirical Essays with a Gender Focus

This dissertation comprises three essays on the Turkish labor market. The first essay characterizes the distinctive characteristics of the Turkish labor market with the aim of understanding the factors lying behind its long-standing poor performance relative to its European counterparts. The analysis is based on a cross-country comparison among selected European Union countries. Among all the indicators of labor market flexibility, non-wage cost rigidities are regarded as one of the most important factors in slowing down employment creation in Turkey. The second essay focuses on an employment subsidy policy which introduces a reduction in non-wage costs through social security premium incentives granted to women and young men. Exploiting a difference-in-difference-in differences strategy, I evaluate the effectiveness of this policy in creating employment for the target group. The results, net of the recent crisis effect, suggest that the policy accounts for a 1.4% to 1.6% increase in the probability of being hired for women aged 30 to 34 above men of the same age group in the periods shortly after the announcement of the policy. In the third essay of the dissertation, I analyze the labor supply response of married women to their husbands' job losses (AWE). I empirically test the hypothesis of added worker effect for the global economic crisis of 2008 by relying on the Turkey context. Identification is achieved by exploiting the exogenous variation in the output of male-dominated sectors hard-hit by the crisis and the gender-segmentation that characterizes the Turkish labor market. Findings based on the instrumental variable approach suggest that the added worker effect explains up to 64% of the observed increase in female labor force participation in Turkey. The size of the effect depends on how long it takes for wives to adjust their labor supply to their husbands' job losses.

Flexibility and firm value: the role of inventories

In the present thesis I study the contribution to firm value of inventories management from a risk management perspective. I find a significant contribution of inventories to the value of risk management especially through the operating flexibility channel. In contrast, I do not find evidence supporting the view of inventories a reserve of liquidity. Inventories substitute, albeit not perfectly, derivatives or cash holdings. The substitution between hedging with derivatives and inventory is moderated by the correlation between cash flow and the underlying asset in the derivative contract. Hedge ratios increase with the effectiveness of derivatives. The decision to hedge with cash holdings or inventories is strongly influenced by the degree of complementarity between production factors and by cash flow volatility. In addition, I provide a risk management based explanation of the secular substitution between inventories and cash holdings documented, among others, in Bates et al. (2009), Journal of Finance. In a sample of U.S. firms between 1980 and 2006, I empirically confirm the negative relation between inventories and cash and provide evidence on the poor performance of investment cash flow sensitivities as a measure of financial constraints also in the case of inventories investment. This result can be explained by firms' scarce reliance on inventories as a reserve of liquidity. Finally, as an extension of my study, I contrast with empirical data the theoretical predictions of a model on the integrated management of inventories, trade credit and cash holdings.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Adipose-derived stem cells and tissue revascularization: enhancing islet survival and performance for diabetes care.

Pancreatic islet transplantation represents a fascinating procedure that, at the moment, can be considered as alternative to standard insulin treatment or pancreas transplantation only for selected categories of patients with type 1 diabetes mellitus. Among the factors responsible for leading to poor islet engraftment, hypoxia plays an important role. Mesenchymal stem cells (MSCs) were recently used in animal models of islet transplantation not only to reduce allograft rejection, but also to promote revascularization. Currently adipose tissue represents a novel and good source of MSCs. Moreover, the capability of adipose-derived stem cells (ASCs) to improve islet graft revascularization was recently reported after hybrid transplantation in mice. Within this context, we have previously shown that hyaluronan esters of butyric and retinoic acids can significantly enhance the rescuing potential of human MSCs. Here we evaluated whether ex vivo preconditioning of human ASCs (hASCs) with a mixture of hyaluronic (HA), butyric (BU), and retinoic (RA) acids may result in optimization of graft revascularization after islet/stem cell intrahepatic cotransplantation in syngeneic diabetic rats. We demonstrated that hASCs exposed to the mixture of molecules are able to increase the secretion of vascular endothelial growth factor (VEGF), as well as the transcription of angiogenic genes, including VEGF, KDR (kinase insert domain receptor), and hepatocyte growth factor (HGF). Rats transplanted with islets cocultured with preconditioned hASCs exhibited a better glycemic control than rats transplanted with an equal volume of islets and control hASCs. Cotransplantation with preconditioned hASCs was also associated with enhanced islet revascularization in vivo, as highlighted by graft morphological analysis. The observed increase in islet graft revascularization and function suggests that our method of stem cell preconditioning may represent a novel strategy to remarkably improve the efficacy of islets-hMSCs cotransplantation.