6 resultados para Instrumental-variable Methods

em Digital Commons at Florida International University


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This dissertation addresses three issues in the political economy of growth literature. The first study empirically tests the hypothesis that income inequality influences the size of a country's sovereign debt for a sample of developing countries for the period 1970–1990. The argument examined is that governments tend to yield to popular pressures to engage in redistributive policies, partially financed by foreign borrowing. Facing increased risk of default, international creditors limit the credit they extend, with the result that borrowing countries invest less and grow at a slower pace. The findings do not seem to support the negative relationship between inequality and sovereign debt, as there is evidence of increases in multilateral, countercyclical flows until the mid 1980s in Latin America. The hypothesis would hold for the period 1983–1990. Debt flows and levels seem to be positively correlated with growth as expected. ^ The second study empirically investigates the hypothesis that pronounced levels of inequality lead to unconsolidated democracies. We test the existence of a nonmonotonic relationship between inequality and democracy for a sample of Latin American countries for the period 1970–2000, where democracy appears to consolidate at some intermediate level of inequality. We find that the nonmonotonic relationship holds using instrumental variables methods. Bolivia seems to be a case of unconsolidated democracy. The positive relationship between per capita income and democracy disappears once fixed effects are introduced. ^ The third study explores the nonlinear relationship between per capita income and private saving levels in Latin America. Several estimation methods are presented; however, only the estimation of a dynamic specification through a state-of-the-art general method of moments estimator yields consistent estimates with increased efficiency. Results support the hypothesis that income positively affects private saving, while system GMM reveals nonlinear effects at income levels that exceed the ones included in this sample for the period 1960–1994. We also find that growth, government dissaving, and tightening of credit constraints have a highly significant and positive effect on private saving. ^

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The Locard exchange principle proposes that a person can not enter or leave an area or come in contact with an object, without an exchange of materials. In the case of scent evidence, the suspect leaves his scent in the location of the crime scene itself or on objects found therein. Human scent evidence collected from a crime scene can be evaluated through the use of specially trained canines to determine an association between the evidence and a suspect. To date, there has been limited research as to the volatile organic compounds (VOCs) which comprise human odor and their usefulness in distinguishing among individuals. For the purposes of this research, human scent is defined as the most abundant volatile organic compounds present in the headspace above collected odor samples. ^ An instrumental method has been created for the analysis of the VOCs present in human scent, and has been utilized for the optimization of materials used for the collection and storage of human scent evidence. This research project has identified the volatile organic compounds present in the headspace above collected scent samples from different individuals and various regions of the body, with the primary focus involving the armpit area and the palms of the hands. Human scent from the armpit area and palms of an individual sampled over time shows lower variation in the relative peak area ratio of the common compounds present than what is seen across a population. A comparison of the compounds present in human odor for an individual over time, and across a population has been conducted and demonstrates that it is possible to instrumentally differentiate individuals based on the volatile organic compounds above collected odor samples. ^

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In certain European countries and the United States of America, canines have been successfully used in human scent identification. There is however, limited scientific knowledge on the composition of human scent and the detection mechanism that produces an alert from canines. This lack of information has resulted in successful legal challenges to human scent evidence in the courts of law. ^ The main objective of this research was to utilize science to validate the current practices of using human scent evidence in criminal cases. The goals of this study were to utilize Headspace Solid Phase Micro Extraction Gas Chromatography Mass Spectrometry (HS-SPME-GC/MS) to determine the optimum collection and storage conditions for human scent samples, to investigate whether the amount of DNA deposited upon contact with an object affects the alerts produced by human scent identification canines, and to create a prototype pseudo human scent which could be used for training purposes. ^ Hand odor samples which were collected on different sorbent materials and exposed to various environmental conditions showed that human scent samples should be stored without prolonged exposure to UVA/UVB light to allow minimal changes to the overall scent profile. Various methods of collecting human scent from objects were also investigated and it was determined that passive collection methods yields ten times more VOCs by mass than active collection methods. ^ Through the use of polymerase chain reaction (PCR) no correlation was found between the amount of DNA that was deposited upon contact with an object and the alerts that were produced by human scent identification canines. Preliminary studies conducted to create a prototype pseudo human scent showed that it is possible to produce fractions of a human scent sample which can be presented to the canines to determine whether specific fractions or the entire sample is needed to produce alerts by the human scent identification canines. ^

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Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

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In certain European countries and the United States of America, canines have been successfully used in human scent identification. There is however, limited scientific knowledge on the composition of human scent and the detection mechanism that produces an alert from canines. This lack of information has resulted in successful legal challenges to human scent evidence in the courts of law. The main objective of this research was to utilize science to validate the current practices of using human scent evidence in criminal cases. The goals of this study were to utilize Headspace Solid Phase Micro Extraction Gas Chromatography Mass Spectrometry (HS-SPME-GC/MS) to determine the optimum collection and storage conditions for human scent samples, to investigate whether the amount of DNA deposited upon contact with an object affects the alerts produced by human scent identification canines, and to create a prototype pseudo human scent which could be used for training purposes. Hand odor samples which were collected on different sorbent materials and exposed to various environmental conditions showed that human scent samples should be stored without prolonged exposure to UVA/UVB light to allow minimal changes to the overall scent profile. Various methods of collecting human scent from objects were also investigated and it was determined that passive collection methods yields ten times more VOCs by mass than active collection methods. Through the use of polymerase chain reaction (PCR) no correlation was found between the amount of DNA that was deposited upon contact with an object and the alerts that were produced by human scent identification canines. Preliminary studies conducted to create a prototype pseudo human scent showed that it is possible to produce fractions of a human scent sample which can be presented to the canines to determine whether specific fractions or the entire sample is needed to produce alerts by the human scent identification canines.

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Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.