10 resultados para regressions

em Duke University


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We develop general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit recent nonparametric asymptotic distributional results, are both easy-to-implement and highly accurate in empirically realistic situations. We also illustrate that properly accounting for the measurement errors in the volatility forecast evaluations reported in the existing literature can result in markedly higher estimates for the true degree of return volatility predictability.

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OBJECTIVE: To assess the effect of bacterial vaginosis (BV) on the risk of high-grade squamous intraepithelial lesions (HSIL) among HIV-seropositive women. METHODS: A hospital-based prospective cohort study of HIV-seropositive women was conducted in Johannesburg, South Africa from January 2005 to September 2009. Multivariate log-binomial and Poisson regressions were used to estimate prevalence and rate ratios, respectively. RESULTS: Among 1954 HIV-seropositive women, the baseline prevalence of HSIL was 17%. BV prevalence was high (54%) and showed no association with prevalence of HSIL (adjusted prevalence ratio, 1.12; 95% confidence intervals (CI), 0.92-1.35) nor with cervical lesion progression at follow-up visit (n=503) (adjusted rate ratio: 1.00; 95% CI, 0.65-1.53). CONCLUSION: Among HIV-seropositive women, BV was not associated with an increased risk of HSIL or cervical lesion progression.

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BACKGROUND: The proportion of births attended by skilled health personnel is one of two indicators used to measure progress towards Millennium Development Goal 5, which aims for a 75% reduction in global maternal mortality ratios by 2015. Rwanda has one of the highest maternal mortality ratios in the world, estimated between 249-584 maternal deaths per 100,000 live births. The objectives of this study were to quantify secular trends in health facility delivery and to identify factors that affect the uptake of intrapartum healthcare services among women living in rural villages in Bugesera District, Eastern Province, Rwanda. METHODS: Using census data and probability proportional to size cluster sampling methodology, 30 villages were selected for community-based, cross-sectional surveys of women aged 18-50 who had given birth in the previous three years. Complete obstetric histories and detailed demographic data were elicited from respondents using iPad technology. Geospatial coordinates were used to calculate the path distances between each village and its designated health center and district hospital. Bivariate and multivariate logistic regressions were used to identify factors associated with delivery in health facilities. RESULTS: Analysis of 3106 lifetime deliveries from 859 respondents shows a sharp increase in the percentage of health facility deliveries in recent years. Delivering a penultimate baby at a health facility (OR = 4.681 [3.204 - 6.839]), possessing health insurance (OR = 3.812 [1.795 - 8.097]), managing household finances (OR = 1.897 [1.046 - 3.439]), attending more antenatal care visits (OR = 1.567 [1.163 - 2.112]), delivering more recently (OR = 1.438 [1.120 - 1.847] annually), and living closer to a health center (OR = 0.909 [0.846 - 0.976] per km) were independently associated with facility delivery. CONCLUSIONS: The strongest correlates of facility-based delivery in Bugesera District include previous delivery at a health facility, possession of health insurance, greater financial autonomy, more recent interactions with the health system, and proximity to a health center. Recent structural interventions in Rwanda, including the rapid scale-up of community-financed health insurance, likely contributed to the dramatic improvement in the health facility delivery rate observed in our study.

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We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Time-varying parameters are linked to latent processes that are thresholded to induce zero values adaptively, providing natural mechanisms for dynamic variable inclusion/selection. We discuss Bayesian model specification, analysis and prediction in dynamic regressions, time-varying vector autoregressions, and multivariate volatility models using latent thresholding. Application to a topical macroeconomic time series problem illustrates some of the benefits of the approach in terms of statistical and economic interpretations as well as improved predictions. Supplementary materials for this article are available online. © 2013 Copyright Taylor and Francis Group, LLC.

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OBJECTIVE: Pathological gaits have been shown to limit transfer between potential (PE) and kinetic (KE) energy during walking, which can increase locomotor costs. The purpose of this study was to examine whether energy exchange would be limited in people with knee osteoarthritis (OA). METHODS: Ground reaction forces during walking were collected from 93 subjects with symptomatic knee OA (self-selected and fast speeds) and 13 healthy controls (self-selected speed) and used to calculate their center of mass (COM) movements, PE and KE relationships, and energy recovery during a stride. Correlations and linear regressions examined the impact of energy fluctuation phase and amplitude, walking velocity, body mass, self-reported pain, and radiographic severity on recovery. Paired t-tests were run to compare energy recovery between cohorts. RESULTS: Symptomatic knee OA subjects displayed lower energetic recovery during self-selected walking speeds than healthy controls (P = 0.0018). PE and KE phase relationships explained the majority (66%) of variance in recovery. Recovery had a complex relationship with velocity and its change across speeds was significantly influenced by the self-selected walking speed of each subject. Neither radiographic OA scores nor subject self-reported measures demonstrated any relationship with energy recovery. CONCLUSIONS: Knee OA reduces effective exchange of PE and KE, potentially increasing the muscular work required to control movements of the COM. Gait retraining may return subjects to more normal patterns of energy exchange and allow them to reduce fatigue.

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We asked 1004 undergraduates to estimate both the probability that they would enter therapy and the probability that they experienced but could not remember incidents of potentially life-threatening childhood traumas or physical and sexual abuse. We found a linear relation between the expectation of entering therapy and the belief that one had, but cannot now remember, childhood trauma and abuse. Thus individuals who are prone to seek psychotherapy are also prone to accept a suggested memory of childhood trauma or abuse as fitting their expectations. In multiple regressions predicting the probability of forgotten memories of childhood traumas and abuse, the expectation of entering therapy remained as a substantial predictor when self-report measures of mood, anxiety, post-traumatic stress disorder symptom severity, and trauma exposure were included.

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This dissertation explores the complex interactions between organizational structure and the environment. In Chapter 1, I investigate the effect of financial development on the formation of European corporate groups. Since cross-country regressions are hard to interpret in a causal sense, we exploit exogenous industry measures to investigate a specific channel through which financial development may affect group affiliation: internal capital markets. Using a comprehensive firm-level dataset on European corporate groups in 15 countries, we find that countries

with less developed financial markets have a higher percentage of group affiliates in more capital intensive industries. This relationship is more pronounced for young and small firms and for affiliates of large and diversified groups. Our findings are consistent with the view that internal capital markets may, under some conditions, be more efficient than prevailing external markets, and that this may drive group affiliation even in developed economies. In Chapter 2, I bridge current streams of innovation research to explore the interplay between R&D, external knowledge, and organizational structure–three elements of a firm’s innovation strategy which we argue should logically be studied together. Using within-firm patent assignment patterns,

we develop a novel measure of structure for a large sample of American firms. We find that centralized firms invest more in research and patent more per R&D dollar than decentralized firms. Both types access technology via mergers and acquisitions, but their acquisitions differ in terms of frequency, size, and i\ntegration. Consistent with our framework, their sources of value creation differ: while centralized firms derive more value from internal R&D, decentralized firms rely more on external knowledge. We discuss how these findings should stimulate more integrative work on theories of innovation. In Chapter 3, I use novel data on 1,265 newly-public firms to show that innovative firms exposed to environments with lower M&A activity just after their initial public offering (IPO) adapt by engaging in fewer technological acquisitions and

more internal research. However, this adaptive response becomes inertial shortly after IPO and persists well into maturity. This study advances our understanding of how the environment shapes heterogeneity and capabilities through its impact on firm structure. I discuss how my results can help bridge inertial versus adaptive perspectives in the study of organizations, by

documenting an instance when the two interact.

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Wetland ecosystems provide many valuable ecosystem services, including carbon (C) storage and improvement of water quality. Yet, restored and managed wetlands are not frequently evaluated for their capacity to function in order to deliver on these values. Specific restoration or management practices designed to meet one set of criteria may yield unrecognized biogeochemical costs or co-benefits. The goal of this dissertation is to improve scientific understanding of how wetland restoration practices and waterfowl habitat management affect critical wetland biogeochemical processes related to greenhouse gas emissions and nutrient cycling. I met this goal through field and laboratory research experiments in which I tested for relationships between management factors and the biogeochemical responses of wetland soil, water, plants and trace gas emissions. Specifically, I quantified: (1) the effect of organic matter amendments on the carbon balance of a restored wetland; (2) the effectiveness of two static chamber designs in measuring methane (CH4) emissions from wetlands; (3) the impact of waterfowl herbivory on the oxygen-sensitive processes of methane emission and coupled nitrification-denitrification; and (4) nitrogen (N) exports caused by prescribed draw down of a waterfowl impoundment.

The potency of CH4 emissions from wetlands raises the concern that widespread restoration and/or creation of freshwater wetlands may present a radiative forcing hazard. Yet data on greenhouse gas emissions from restored wetlands are sparse and there has been little investigation into the greenhouse gas effects of amending wetland soils with organic matter, a recent practice used to improve function of mitigation wetlands in the Eastern United States. I measured trace gas emissions across an organic matter gradient at a restored wetland in the coastal plain of Virginia to test the hypothesis that added C substrate would increase the emission of CH4. I found soils heavily loaded with organic matter emitted significantly more carbon dioxide than those that have received little or no organic matter. CH4 emissions from the wetland were low compared to reference wetlands and contrary to my hypothesis, showed no relationship with the loading rate of added organic matter or total soil C. The addition of moderate amounts of organic matter (< 11.2 kg m-2) to the wetland did not greatly increase greenhouse gas emissions, while the addition of high amounts produced additional carbon dioxide, but not CH4.

I found that the static chambers I used for sampling CH4 in wetlands were highly sensitive to soil disturbance. Temporary compression around chambers during sampling inflated the initial chamber CH4 headspace concentration and/or lead to generation of nonlinear, unreliable flux estimates that had to be discarded. I tested an often-used rubber-gasket sealed static chamber against a water-filled-gutter seal chamber I designed that could be set up and sampled from a distance of 2 m with a remote rod sampling system to reduce soil disturbance. Compared to the conventional design, the remotely-sampled static chambers reduced the chance of detecting inflated initial CH4 concentrations from 66 to 6%, and nearly doubled the proportion of robust linear regressions from 45 to 86%. The new system I developed allows for more accurate and reliable CH4 sampling without costly boardwalk construction.

I explored the relationship between CH4 emissions and aquatic herbivores, which are recognized for imposing top-down control on the structure of wetland ecosystems. The biogeochemical consequences of herbivore-driven disruption of plant growth, and in turn, mediated oxygen transport into wetland sediments, were not previously known. Two growing seasons of herbivore exclusion experiments in a major waterfowl overwintering wetland in the Southeastern U.S. demonstrate that waterfowl herbivory had a strong impact on the oxygen-sensitive processes of CH4 emission and nitrification. Denudation by herbivorous birds increased cumulative CH4 flux by 233% (a mean of 63 g CH4 m-2 y-1) and inhibited coupled nitrification-denitrification, as indicated by nitrate availability and emissions of nitrous oxide. The recognition that large populations of aquatic herbivores may influence the capacity for wetlands to emit greenhouse gases and cycle nitrogen is particularly salient in the context of climate change and nutrient pollution mitigation goals. For example, our results suggest that annual emissions of 23 Gg of CH4 y-1 from ~55,000 ha of publicly owned waterfowl impoundments in the Southeastern U.S. could be tripled by overgrazing.

Hydrologically controlled moist-soil impoundment wetlands provide critical habitat for high densities of migratory bird populations, thus their potential to export nitrogen (N) to downstream waters may contribute to the eutrophication of aquatic ecosystems. To investigate the relative importance of N export from these built and managed habitats, I conducted a field study at an impoundment wetland that drains into hypereutrophic Lake Mattamuskeet. I found that prescribed hydrologic drawdowns of the impoundment exported roughly the same amount of N (14 to 22 kg ha-1) as adjacent fertilized agricultural fields (16 to 31 kg ha-1), and contributed approximately one-fifth of total N load (~45 Mg N y-1) to Lake Mattamuskeet. Ironically, the prescribed drawdown regime, designed to maximize waterfowl production in impoundments, may be exacerbating the degradation of habitat quality in the downstream lake. Few studies of wetland N dynamics have targeted impoundments managed to provide wildlife habitat, but a similar phenomenon may occur in some of the 36,000 ha of similarly-managed moist-soil impoundments on National Wildlife Refuges in the southeastern U.S. I suggest early drawdown as a potential method to mitigate impoundment N pollution and estimate it could reduce N export from our study impoundment by more than 70%.

In this dissertation research I found direct relationships between wetland restoration and impoundment management practices, and biogeochemical responses of greenhouse gas emission and nutrient cycling. Elevated soil C at a restored wetland increased CO2 losses even ten years after the organic matter was originally added and intensive herbivory impact on emergent aquatic vegetation resulted in a ~230% increase in CH4 emissions and impaired N cycling and removal. These findings have important implications for the basic understanding of the biogeochemical functioning of wetlands and practical importance for wetland restoration and impoundment management in the face of pressure to mitigate the environmental challenges of global warming and aquatic eutrophication.

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The ideal conception of a judge is that of a neutral arbitrator. However, there exist good reasons to believe that personal characteristics, including professional experiences, bias judges. Such suspicions inspired two hypotheses: (1) judges that are former prosecutors are biased in favor of the government in criminal appeals; (2) judges that are former criminal defense attorneys are biased in favor of the criminal appellant. These hypotheses were tested by gathering professional information about state supreme court judges in the south during the years from 1995 until 1998. That was then matched to an existing database that recorded those judges’ demographics and decisions in criminal appeals during that time. Logistic regressions of that data revealed that despite when other characteristics, including gender, race, and legal experience, were accounted for, criminal defense remained a statistically significant predictor. Judges with a background in criminal defense were more likely to reverse criminal court decisions. In contrast, prosecutorial experience was not a good predictor of how a judge ruled. Judges that had backgrounds in prosecution did not rule much differently than those that did not have such a background.

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I develop a new methodology for measuring tail risks using the cross section of bid-ask spreads. Market makers embed tail risk information into spreads because (1) they lose to arbitrageurs when changes to asset values exceed the cost of liquidity and (2) underlying price movements and potential costs are linear in factor loadings. Using this insight, simple cross-sectional regressions relating spreads and trading volume to factor betas can recover tail risks in real time for priced or non-priced return factors. The methodology disentangles financial and aggregate market risks during the 2007-2008 Financial Crisis; anticipates jump risks associated with Federal Open Market Committee announcements; and quantifies a sharp, temporary increase in market tail risk before and throughout the 2010 Flash Crash. The recovered time series of implied market risks also aligns closely with both realized market jumps and the VIX.