Determining the effect of regulation on Microfinance Institutions Financial Self-Sustainability. A Cross-Country Comparison

Microfinance is an initiative which seeks to address financial inclusion, micro-entrepreneurship, and poverty reduction without over burdening governments. However, the current sector of microfinance is still heavily dependent on the good will of donors. The over-reliance on donations is a feature which threatens the long term sustainability of microfinance. Much has been written about this reliance, but research to date hasn’t empirically examined the effect of regulation as a mediator. This is a critical area of study because regulation directly affects Microfinance Institutions’ (MFI) innovation, and innovation is what shapes the future of microfinance. This thesis considers the role that regulation plays in affecting MFI’s and their ability to innovate in products, services and long-term sustainability via access to capital. Interviews were undertaken with stakeholders in MFI’s, NGO’s, Self-Regulating Bodies, and Regulators in India, Pakistan, and Bangladesh. This thesis discusses findings from interviews in relation to regulatory measures regarding financial self-sustainability of MFI’s. The conclusions of this thesis have implications for policy and inform the microfinance literature.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

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.

IGF system, CD99 and tumor-specific chromosomal translocations: evaluation of their cross-talk and definition of their role in Ewing sarcoma and prostate cancer

Aberrant expression of ETS transcription factors, including FLI1 and ERG, due to chromosomal translocations has been described as a driver event in initiation and progression of different tumors. In this study, the impact of prostate cancer (PCa) fusion gene TMPRSS2-ERG was evaluated on components of the insulin-like growth factor (IGF) system and the CD99 molecule, two well documented targets of EWS-FLI1, the hallmark of Ewing sarcoma (ES). The aim of this study was to identify common or distinctive ETS-related mechanisms which could be exploited at biological and clinical level. The results demonstrate that IGF-1R represents a common target of ETS rearrangements as ERG and FLI1 bind IGF-1R gene promoter and their modulation causes alteration in IGF-1R protein levels. At clinical level, this mechanism provides basis for a more rationale use of anti-IGF-1R inhibitors as PCa cells expressing the fusion gene better respond to anti-IGF-1R agents. EWS-FLI1/IGF-1R axis provides rationale for combination of anti-IGF-1R agents with trabectedin, an alkylator agent causing enhanced EWS-FLI1 occupancy on the IGF-1R promoter. TMPRSS2-ERG also influences prognosis relevance of IGF system as high IGF-1R correlates with a better biochemical progression free survival (BPFS) in PCa patients negative for the fusion gene while marginal or no association was found in the total cases or TMPRSS2-ERG-positive cases, respectively. This study indicates CD99 is differentially regulated between ETS-related tumors as CD99 is not a target of ERG. In PCa, CD99 did not show differential expression between TMPRSS2-ERG-positive and –negative cells. A direct correlation was anyway found between ERG and CD99 proteins both in vitro and in patients putatively suggesting that ERG target genes comprehend regulators of CD99. Despite a little trend suggesting a correlation between CD99 expression and a better BPFS, no clinical relevance for CD99 was found in the field of prognostic biomarkers.