932 resultados para Short and Long Interest Rates
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Technological advances during the past 30 years have dramatically improved survival rates for children with life-threatening conditions (preterm births, congenital anomalies, disease, or injury) resulting in children with special health care needs (CSHCN), children who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who require health and related services beyond that required by children generally. There are approximately 10.2 million of these children in the United States or one in five households with a child with special health care needs. Care for these children is limited to home care, medical day care (Prescribed Pediatric Extended Care; P-PEC) or a long term care (LTC) facility. There is very limited research examining health outcomes of CSHCN and their families. The purpose of this research was to compare the effects of home care settings, P-PEC settings, and LTC settings on child health and functioning, family health and function, and health care service use of families with CSHCN. Eighty four CSHCN ages 2 to 21 years having a medically fragile or complex medical condition that required continual monitoring were enrolled with their parents/guardians. Interviews were conducted monthly for five months using the PedsQL™ Generic Core Module for child health and functioning, PedsQL™ Family Impact Module for family health and functioning, and Access to Care from the NS-CSHCN survey for health care services. Descriptive statistics, chi square, and ANCOVA were conducted to determine differences across care settings. Children in the P-PEC settings had a highest health care quality of life (HRQL) overall including physical and psychosocial functioning. Parents/guardians with CSHCN in LTC had the highest HRQL including having time and energy for a social life and employment. Parents/guardians with CSHCN in home care settings had the poorest HRQL including physical and psychosocial functioning with cognitive difficulties, difficulties with worry, communication, and daily activities. They had the fewest hours of employment and the most hours providing direct care for their children. Overall health care service use was the same across the care settings.
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The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.
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Single-molecule manipulation experiments of molecular motors provide essential information about the rate and conformational changes of the steps of the reaction located along the manipulation coordinate. This information is not always sufficient to define a particular kinetic cycle. Recent single-molecule experiments with optical tweezers showed that the DNA unwinding activity of a Phi29 DNA polymerase mutant presents a complex pause behavior, which includes short and long pauses. Here we show that different kinetic models, considering different connections between the active and the pause states, can explain the experimental pause behavior. Both the two independent pause model and the two connected pause model are able to describe the pause behavior of a mutated Phi29 DNA polymerase observed in an optical tweezers single-molecule experiment. For the two independent pause model all parameters are fixed by the observed data, while for the more general two connected pause model there is a range of values of the parameters compatible with the observed data (which can be expressed in terms of two of the rates and their force dependencies). This general model includes models with indirect entry and exit to the long-pause state, and also models with cycling in both directions. Additionally, assuming that detailed balance is verified, which forbids cycling, this reduces the ranges of the values of the parameters (which can then be expressed in terms of one rate and its force dependency). The resulting model interpolates between the independent pause model and the indirect entry and exit to the long-pause state model
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The economic rationale for public intervention into private markets through price mechanisms is twofold: to correct market failures and to redistribute resources. Financial incentives are one such price mechanism. In this dissertation, I specifically address the role of financial incentives in providing social goods in two separate contexts: a redistributive policy that enables low income working families to access affordable childcare in the US and an experimental pay-for-performance intervention to improve population health outcomes in rural India. In the first two papers, I investigate the effects of government incentives for providing grandchild care on grandmothers’ short- and long-term outcomes. In the third paper, coauthored with Manoj Mohanan, Grant Miller, Katherine Donato, and Marcos Vera-Hernandez, we use an experimental framework to consider the the effects of financial incentives in improving maternal and child health outcomes in the Indian state of Karnataka.
Grandmothers provide a significant amount of childcare in the US, but little is known about how this informal, and often uncompensated, time transfer impacts their economic and health outcomes. The first two chapters of this dissertation address the impact of federally funded, state-level means-tested programs that compensate grandparent-provided childcare on the retirement security of older women, an economically vulnerable group of considerable policy interest. I use the variation in the availability and generosity of childcare subsidies to model the effect of government payments for grandchild care on grandmothers’ time use, income, earnings, interfamily transfers, and health outcomes. After establishing that more generous government payments induce grandmothers to provide more hours of childcare, I find that grandmothers adjust their behavior by reducing their formal labor supply and earnings. Grandmothers make up for lost earnings by claiming Social Security earlier, increasing their reliance on Supplemental Security Income (SSI) and reducing financial transfers to their children. While the policy does not appear to negatively impact grandmothers’ immediate economic well-being, there are significant costs to the state, in terms of both up-front costs for care payments and long-term costs as a result of grandmothers’ increased reliance on social insurance.
The final paper, The Role of Non-Cognitive Traits in Response to Financial Incentives: Evidence from a Randomized Control Trial of Obstetrics Care Providers in India, is coauthored with Manoj Mohanan, Grant Miller, Katherine Donato and Marcos Vera-Hernandez. We report the results from “Improving Maternal and Child Health in India: Evaluating Demand and Supply Side Strategies” (IMACHINE), a randomized controlled experiment designed to test the effectiveness of supply-side incentives for private obstetrics care providers in rural Karnataka, India. In particular, the experimental design compares two different types of incentives: (1) those based on the quality of inputs providers offer their patients (inputs contracts) and (2) those based on the reduction of incidence of four adverse maternal and neonatal health outcomes (outcomes contracts). Along with studying the relative effectiveness of the different financial incentives, we also investigate the role of provider characteristics, preferences, expectations and non-cognitive traits in mitigating the effects of incentive contracts.
We find that both contract types input incentive contracts reduce rates of post-partum hemorrhage, the leading cause of maternal mortality in India by about 20%. We also find some evidence of multitasking as output incentive contract providers reduce the level of postnatal newborn care received by their patients. We find that patient health improvements in response to both contract types are concentrated among higher trained providers. We find improvements in patient care to be concentrated among the lower trained providers. Contrary to our expectations, we also find improvements in patient health to be concentrated among the most risk averse providers, while more patient providers respond relatively little to the incentives, and these difference are most evident in the outputs contract arm. The results are opposite for patient care outcomes; risk averse providers have significantly lower rates of patient care and more patient providers provide higher quality care in response to the outputs contract. We find evidence that overconfidence among providers about their expectations about possible improvements reduces the effectiveness of both types of incentive contracts for improving both patient outcomes and patient care. Finally, we find no heterogeneous response based on non-cognitive traits.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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PURPOSE: Conduct a meta-analysis to study the prognostic influence of a previous coronary artery bypass grafting (CABG) in patients admitted for an acute coronary syndrome (ACS). METHODS: A systematic review of the literature was performed using electronic reference databases through January 2013 (MEDLINE, Cochrane Library, Web of Knowledge, Google Scholar and references cited in other studies). Studies in which ACS outcomes with a previous history of CABG were compared with ACS outcomes with no history of previous CABG were considered for inclusion. The main endpoints of interest were mortality and non-fatal acute myocardial infarction. Data was aggregated at three follow-up times using random-effects meta-analysis models. RESULTS: Twenty-four studies were included which provided 387,181 patients for analysis. Previous CABG ACS patients were older, more diabetic and had a more frequent history of a previous myocardial infarction. Pooled in-hospital mortality was higher for the previous CABG ACS patients (OR 1.22 [1.04-1.44], p<0.01, I(2) 88%). The pooled adjusted OR showed no significant differences for the two groups (adjusted OR 1.13 [0.93-1.37], p=0.22, I(2) 92%). Previous CABG ACS patient had a higher pooled 30-day mortality (OR 1.28 [1.05-1.55], p=0.02, I(2) 74%); a higher non-adjusted (OR 1.61 [1.38-1.88], p<0.01, I(2) 70%) and adjusted (adjusted OR 1.37 [1.15-1.65], p<0.01, I(2) 0%) long-term mortality. Both the in-hospital and the long-term re-infarction rates were higher for the previous CABG ACS patients. CONCLUSIONS: According to our data, ACS patients with previous CABG history had a higher risk for short- and long-term adverse events.
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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.
Resumo:
This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.
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Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.
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This research explores the business model (BM) evolution process of entrepreneurial companies and investigates the relationship between BM evolution and firm performance. Recently, it has been increasingly recognised that the innovative design (and re-design) of BMs is crucial to the performance of entrepreneurial firms, as BM can be associated with superior value creation and competitive advantage. However, there has been limited theoretical and empirical evidence in relation to the micro-mechanisms behind the BM evolution process and the entrepreneurial outcomes of BM evolution. This research seeks to fill this gap by opening up the ‘black box’ of the BM evolution process, exploring the micro-patterns that facilitate the continuous shaping, changing, and renewing of BMs and examining how BM evolutions create and capture value in a dynamic manner. Drawing together the BM and strategic entrepreneurship literature, this research seeks to understand: (1) how and why companies introduce BM innovations and imitations; (2) how BM innovations and imitations interplay as patterns in the BM evolution process; and (3) how BM evolution patterns affect firm performances. This research adopts a longitudinal multiple case study design that focuses on the emerging phenomenon of BM evolution. Twelve entrepreneurial firms in the Chinese Online Group Buying (OGB) industry were selected for their continuous and intensive developments of BMs and their varying success rates in this highly competitive market. Two rounds of data collection were carried out between 2013 and 2014, which generates 31 interviews with founders/co-founders and in total 5,034 pages of data. Following a three-stage research framework, the data analysis begins by mapping the BM evolution process of the twelve companies and classifying the changes in the BMs into innovations and imitations. The second stage focuses down to the BM level, which addresses the BM evolution as a dynamic process by exploring how BM innovations and imitations unfold and interplay over time. The final stage focuses on the firm level, providing theoretical explanations as to the effects of BM evolution patterns on firm performance. This research provides new insights into the nature of BM evolution by elaborating on the missing link between BM dynamics and firm performance. The findings identify four patterns of BM evolution that have different effects on a firm’s short- and long-term performance. This research contributes to the BM literature by presenting what the BM evolution process actually looks like. Moreover, it takes a step towards the process theory of the interplay between BM innovations and imitations, which addresses the role of companies’ actions, and more importantly, reactions to the competitors. Insights are also given into how entrepreneurial companies achieve and sustain value creation and capture by successfully combining the BM evolution patterns. Finally, the findings on BM evolution contributes to the strategic entrepreneurship literature by increasing the understanding of how companies compete in a more dynamic and complex environment. It reveals that, the achievement of superior firm performance is more than a simple question of whether to innovate or imitate, but rather an integration of innovation and imitation strategies over time. This study concludes with a discussion of the findings and their implications for theory and practice.
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This paper studies monetary policy transmission using several statistical tools -- We find that the relationships between the policy interest rate and the financial system’s interest rates are positive and statistically significant, and transmission is complete eight months after policy shocks occur -- The speed of transmission varies according to the type of interest rates -- Transmission is faster for interest rates on loans provided to households, and is particularly rapid and complete for rates on preferential commercial loans -- Transmission is slower for credit card and mortgage rates, due to regulatory issues (interest rate ceilings)
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Long-term success of family firms is of utmost social and economic importance. Three of its determinants are in the center of this Dissertation: firmlevel entrepreneurial orientation (EO), managers' entrepreneurial behavior, and value-creating attitudes of non-family employees. Each determinant and respective research gaps are addressed by one paper of this cumulative dissertation. Referring to firm-level EO, scholars claim that EO is a main antecedent to firms' both short- and long-term success. However, family firms seem to be successful across generations despite rather low levels of EO. The first paper addresses this paradox by investigating EO patterns of long-lived family firms in three Swiss case studies. The main finding is that the key to success is not to be as entrepreneurially as possible all the time, but to continuously adapt the EO profile depending on internal and external factors. Moreover, the paper suggest new subcategories to different EO dimensions. With regard to entrepreneurial behavior of managers, there is a lack of knowledge how individual-level and organizational level factors affect its evolvement. The second paper addresses this gap by investigating a sample of 403 middle-level managers from both family and non-family firms. It introduces psychological ownership of managers as individual-level antecedent and investigates the interaction with organizational factors. As a central insight, management support is found to strengthen the psychological ownership-entrepreneurial behavior relationship. The third paper is based on the fact that employees' justice perceptions are established antecedents of value-creating employee attitudes such as affective commitment and job satisfaction. Even though family firms are susceptible to nonfamily employees´ perceptions of injustice, corresponding research is scarce. Moreover, the mechanism connecting justice perceptions and positive outcomes is still unclear. Addressing these gaps, the analysis of a sample of 310 non-family employees reveals that psychological ownership is a mediator in the relationships between distributive justice perceptions and both affective commitment and job satisfaction. Altogether, the three papers offer valuable contributions to family business literature with respect to EO, entrepreneurial behavior, and value-creating employee attitudes. Thus, they increase current understanding about important determinants of family firms' long-term success, while opening up numerous ways of future research.
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An innovative approach to quantify interest rate sensitivities of emerging market corporates is proposed. Our focus is centered at price sensitivity of modeled investment grade and high yield portfolios to changes in the present value of modeled portfolios composed of safe-haven assets, which define risk-free interest rates. Our methodology is based on blended yield indexes. Modeled investment horizons are always kept above one year thus allowing to derive empirical implications for practical strategies of interest rate risk management in the banking book. As our study spans over the period 2002 – 2015, it covers interest rate sensitivity of assets under the pre-crisis, crisis, and post-crisis phases of the economic cycles. We demonstrate that the emerging market corporate bonds both, investment grade and high yield types, depending on the phase of a business cycle exhibit diverse regimes of sensitivity to interest rate changes. We observe switching from a direct positive sensitivity under the normal pre-crisis market conditions to an inverted negative sensitivity during distressed turmoil of the recent financial crisis, and than back to direct positive but weaker sensitivity under new normal post-crisis conjuncture. Our unusual blended yield-based approach allows us to present theoretical explanations of such phenomena from economics point of view and helps us to solve an old controversy regarding positive or negative responses of credit spreads to interest rates. We present numerical quantification of sensitivities, which corroborate with our conclusion that hedging of interest rate risk ought to be a dynamic process linked to the phases of business cycles as we evidence a binary-like behavior of interest rate sensitivities along the economic time. Our findings allow banks and financial institutions for approaching downside risk management and optimizing economic capital under Basel III regulatory capital rules.
Resumo:
Technological advances during the past 30 years have dramatically improved survival rates for children with life-threatening conditions (preterm births, congenital anomalies, disease, or injury) resulting in children with special health care needs (CSHCN), children who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who require health and related services beyond that required by children generally. There are approximately 10.2 million of these children in the United States or one in five households with a child with special health care needs. Care for these children is limited to home care, medical day care (Prescribed Pediatric Extended Care; P-PEC) or a long term care (LTC) facility. There is very limited research examining health outcomes of CSHCN and their families. The purpose of this research was to compare the effects of home care settings, P-PEC settings, and LTC settings on child health and functioning, family health and function, and health care service use of families with CSHCN. Eighty four CSHCN ages 2 to 21 years having a medically fragile or complex medical condition that required continual monitoring were enrolled with their parents/guardians. Interviews were conducted monthly for five months using the PedsQL TM Generic Core Module for child health and functioning, PedsQL TM Family Impact Module for family health and functioning, and Access to Care from the NS-CSHCN survey for health care services. Descriptive statistics, chi square, and ANCOVA were conducted to determine differences across care settings. Children in the P-PEC settings had a highest health care quality of life (HRQL) overall including physical and psychosocial functioning. Parents/guardians with CSHCN in LTC had the highest HRQL including having time and energy for a social life and employment. Parents/guardians with CSHCN in home care settings had the poorest HRQL including physical and psychosocial functioning with cognitive difficulties, difficulties with worry, communication, and daily activities. They had the fewest hours of employment and the most hours providing direct care for their children. Overall health care service use was the same across the care settings.