Gold and the Stock Market: 3 Essays on Gold Investments

This thesis gives an overview of the history of gold per se, of gold as an investment good and offers some institutional details about gold and other precious metal markets. The goal of this study is to investigate the role of gold as a store of value and hedge against negative market movements in turbulent times. I investigate gold’s ability to act as a safe haven during periods of financial stress by employing instrumental variable techniques that allow for time varying conditional covariance. I find broad evidence supporting the view that gold acts as an anchor of stability during market downturns. During periods of high uncertainty and low stock market returns, gold tends to have higher than average excess returns. The effectiveness of gold as a safe haven is enhanced during periods of extreme crises: the largest peaks are observed during the global financial crises of 2007-2009 and, in particular, during the Lehman default (October 2008). A further goal of this thesis is to investigate whether gold provides protection from tail risk. I address the issue of asymmetric precious metal behavior conditioned to stock market performance and provide empirical evidence about the contribution of gold to a portfolio’s systematic skewness and kurtosis. I find that gold has positive coskewness with the market portfolio when the market is skewed to the left. Moreover, gold shows low cokurtosis with the market returns during volatile periods. I therefore show that gold is a desirable investment good to risk averse investors, since it tends to decrease the probability of experiencing extreme bad outcomes, and the magnitude of losses in case such events occur. Gold thus bears very important and under-researched characteristics as an asset class per se, which this thesis contributed to address and unveil.

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.

Essays in policy evaluation

This dissertation consists of three empirical studies that aim at providing new evidence in the field of public policy evaluation. In particular, the first two chapters focus on the effects of the European cohesion policy, while the third chapter assesses the effectiveness of Italian labour market incentives in reducing long-term unemployment. The first study analyses the effect of EU funds on life satisfaction across European regions , under the assumption that projects financed by structural funds in the fields of employment, education, health and environment may affect the overall quality of life in recipient regions. Using regional data from the European Social Survey in 2002-2006, it resorts to a regression discontinuity design, where the discontinuity is provided by the institutional framework of the policy. The second study aims at estimating the impact of large transfers from a centralized authority to a local administration on the incidence of white collar crimes. It merges a unique dataset on crimes committed in Italian municipalities between 2007 and 2011 with information on the disbursement of EU structural funds in 2007-2013 programming period, employing an instrumental variable estimation strategy that exploits the variation in the electoral cycle at local level. The third study analyses the impact of an Italian labour market policy that allowed firms to cut their labour costs on open-ended job contracts when hiring long-term unemployed workers. It takes advantage of a unique dataset that draws information from the unemployment lists in Veneto region and it resorts to a regression discontinuity approach to estimate the effect of the policy on the job finding rate of long-term unemployed workers.

Timeliness, efficiency and public procurement in hip surgery in Italy

Considering different perspectives, the scope of this thesis is to investigate how to improve healthcare resources allocation and the provision efficiency for hip surgeries, a resource-intensive operation, among the most frequently performed on the elderly, with a trend in volume that is increasing in years due to population aging. Firstly, the effect of Time-To-Surgery (TTS) on mortality for hip fracture patients is investigated. The analysis attempts to account for TTS endogeneity due to the inability to fully control for variables affecting patient delay – e.g. patient severity. Exploiting an instrumental variable model, where being admitted on Friday or Saturday predicts longer TTS, findings show exogenous TTS does not have a significant effect on mortality. Thus suggesting surgeons prioritize patients effectively, neutralizing the adverse impact of longer TTS. Then, the volume-outcome relation for total hip replacement surgery is analyzed, seeking to account for selective referral, which may be present in elective surgery context, and induce reverse causality issue in the volume-outcome relation. The analysis employs a conditional choice model where patient travel distance from all regions' hospitals is used as a hospital choice predictor. Findings show the exogenous hospital volume significantly decreases adverse outcomes probability, especially in the short run. Finally, the change in public procurement design enforced in the Romagna LHA (Italy) is exploited to assess its impact on hip prostheses cost, surgeons' implant choice, and patient health outcomes. Hip prostheses are the major cost-driver of hip replacement surgeries, hence it is crucial to design the public tender such that implant prices are minimized, but cost-containment policies have to be weighted with patient well-being. Evidence shows that a cost reduction occurred without a significant surgeons’ choices impact. Positive or no effect of surgeons specialization is found on patients outcomes after the new procurement introduction.

Application of different instrumental techniques to the selective evaluation of bio-sensible compounds in foodstuff of animal and vegetable origin

This PhD thesis describes the application of some instrumental analytical techniques suitable to the study of fundamental food products for the human diet, such as: extra virgin olive oil and dairy products. These products, widely spread in the market and with high nutritional values, are increasingly recognized healthy properties although their lipid fraction might contain some unfavorable components to the human health. The research activity has been structured in the following investigations: “Comparison of different techniques for trans fatty acids analysis” “Fatty acids analysis of outcrop milk cream samples, with particular emphasis on the content of Conjugated Linoleic Acid (CLA) and trans Fatty Acids (TFA), by using 100m high-polarity capillary column” “Evaluation of the oxidited fatty acids (OFA) content during the Parmigiano-Reggiano cheese seasoning” “Direct analysis of 4-desmethyl sterols and two dihydroxy triterpenes in saponified vegetal oils (olive oil and others) using liquid chromatography-mass spectrometry” “Quantitation of long chain poly-unsatured fatty acids (LC-PUFA) in base infant formulas by Gas Chromatography, and evaluation of the blending phases accuracy during their preparation” “Fatty acids composition of Parmigiano Reggiano cheese samples, with emphasis on trans isomers (TFA)”

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Induction Motor Diagnosis in Variable Speed Drives

Several diagnostic techniques are presented for the detection of electrical fault in induction motor variable speed drives. These techinques are developed taking into account the impact of the control system on machine variables and non stationary operating conditions.

A bayesian model for mixed responses and skew laten variable to measure HRQoL in children

The aim of the thesi is to formulate a suitable Item Response Theory (IRT) based model to measure HRQoL (as latent variable) using a mixed responses questionnaire and relaxing the hypothesis of normal distributed latent variable. The new model is a combination of two models already presented in literature, that is, a latent trait model for mixed responses and an IRT model for Skew Normal latent variable. It is developed in a Bayesian framework, a Markov chain Monte Carlo procedure is used to generate samples of the posterior distribution of the parameters of interest. The proposed model is test on a questionnaire composed by 5 discrete items and one continuous to measure HRQoL in children, the EQ-5D-Y questionnaire. A large sample of children collected in the schools was used. In comparison with a model for only discrete responses and a model for mixed responses and normal latent variable, the new model has better performances, in term of deviance information criterion (DIC), chain convergences times and precision of the estimates.

Development of instrumental and sensory analytical methods of food obtained by traditional and emerging technologies

The consumer demand for natural, minimally processed, fresh like and functional food has lead to an increasing interest in emerging technologies. The aim of this PhD project was to study three innovative food processing technologies currently used in the food sector. Ultrasound-assisted freezing, vacuum impregnation and pulsed electric field have been investigated through laboratory scale systems and semi-industrial pilot plants. Furthermore, analytical and sensory techniques have been developed to evaluate the quality of food and vegetable matrix obtained by traditional and emerging processes. Ultrasound was found to be a valuable technique to improve the freezing process of potatoes, anticipating the beginning of the nucleation process, mainly when applied during the supercooling phase. A study of the effects of pulsed electric fields on phenol and enzymatic profile of melon juice has been realized and the statistical treatment of data was carried out through a response surface method. Next, flavour enrichment of apple sticks has been realized applying different techniques, as atmospheric, vacuum, ultrasound technologies and their combinations. The second section of the thesis deals with the development of analytical methods for the discrimination and quantification of phenol compounds in vegetable matrix, as chestnut bark extracts and olive mill waste water. The management of waste disposal in mill sector has been approached with the aim of reducing the amount of waste, and at the same time recovering valuable by-products, to be used in different industrial sectors. Finally, the sensory analysis of boiled potatoes has been carried out through the development of a quantitative descriptive procedure for the study of Italian and Mexican potato varieties. An update on flavour development in fresh and cooked potatoes has been realized and a sensory glossary, including general and specific definitions related to organic products, used in the European project Ecropolis, has been drafted.

Pulsating variable stars as tracers of galactic structure and interaction mechanisms

My PhD project has been focused on the study of the pulsating variable stars in two ultra-faint dwarf spheroidal satellites of the Milky Way, namely, Leo IV and Hercules; and in two fields of the Large Magellanic Cloud (namely, the Gaia South Ecliptic Pole calibration field, and the 30 Doradus region) that were repeatedly observed in the KS band by the VISTA Magellanic Cloud (VMC, PI M.R. Cioni) survey of the Magellanic System.

Sensory and instrumental profiling of apples: a new tool for quality assessment

Food suppliers currently measure apple quality considering basic pomological descriptors. Sensory analysis is expensive, does not permit to analyse many samples, and cannot be implemented for measuring quality properties in real time. However, sensory analysis is the best way to precisely describe food eating quality, since it is able to define, measure, and explain what is really perceivable by human senses and using a language that closely reflects the consumers’ perception. On the basis of such observations, we developed a detailed protocol for apple sensory profiling by descriptive sensory analysis and instrumental measurements. The collected sensory data were validated by applying rigorous scientific criteria for sensory analysis. The method was then applied for studying sensory properties of apples and their changes in relation to different pre- and post-harvest factors affecting fruit quality, and demonstrated to be able to discriminate fruit varieties and to highlight differences in terms of sensory properties. The instrumental measurements confirmed such results. Moreover, the correlation between sensory and instrumental data was studied, and a new effective approach was defined for the reliable prediction of sensory properties by instrumental characterisation. It is therefore possible to propose the application of this sensory-instrumental tool to all the stakeholders involved in apple production and marketing, to have a reliable description of apple fruit quality.

A multi-instrumental approach to the study of equatorial ionosphere over South America

An extensive study of the morphology and the dynamics of the equatorial ionosphere over South America is presented here. A multi parametric approach is used to describe the physical characteristics of the ionosphere in the regions where the combination of the thermospheric electric field and the horizontal geomagnetic field creates the so-called Equatorial Ionization Anomalies. Ground based measurements from GNSS receivers are used to link the Total Electron Content (TEC), its spatial gradients and the phenomenon known as scintillation that can lead to a GNSS signal degradation or even to a GNSS signal ‘loss of lock’. A new algorithm to highlight the features characterizing the TEC distribution is developed in the framework of this thesis and the results obtained are validated and used to improve the performance of a GNSS positioning technique (long baseline RTK). In addition, the correlation between scintillation and dynamics of the ionospheric irregularities is investigated. By means of a software, here implemented, the velocity of the ionospheric irregularities is evaluated using high sampling rate GNSS measurements. The results highlight the parallel behaviour of the amplitude scintillation index (S4) occurrence and the zonal velocity of the ionospheric irregularities at least during severe scintillations conditions (post-sunset hours). This suggests that scintillations are driven by TEC gradients as well as by the dynamics of the ionospheric plasma. Finally, given the importance of such studies for technological applications (e.g. GNSS high-precision applications), a validation of the NeQuick model (i.e. the model used in the new GALILEO satellites for TEC modelling) is performed. The NeQuick performance dramatically improves when data from HF radar sounding (ionograms) are ingested. A custom designed algorithm, based on the image recognition technique, is developed to properly select the ingested data, leading to further improvement of the NeQuick performance.