Dividends, trust, and firm value

We find evidence that investors value dividends differently depending on their level of trust. Our tests indicate that investor demand for dividend-paying stocks increases as trust decreases, and that this relationship affects market values. We begin with survey evidence showing that people think accounting fraud is less likely among dividend payers and that people with low trust are more likely to hold dividend-paying stocks. We then empirically exploit accounting fraud discoveries within a mutual fund’s portfolio as a shock to trust. In response to these shocks, we show that mutual funds tilt their portfolios toward dividend-paying stocks. This result is not explained by a shift in risk preferences, indicating that these institutional investors are seeking dividends in particular rather than stable firms that just happen to pay dividends. Finally, we provide evidence that dividend payers experience a premium in their market values relative to non-payers when their investor base becomes less trusting

Isolation, Characterization, and Antibiotic Activity of Fungal Metabolites from an Algal Endophyte

Pseudomonas aeruginosa is a gram-negative nosocomial pathogenic bacterium known for its resilience against antibiotics. The bacterium infects over 50,000 patients each year in the United States, with 13% of reported cases involving multi-drug-resistant strains of Pseudomonas. This research discovered several fungal natural products with promising activity against Pseudomonas aeruginosa. The compounds were produced by fungus GOZO23y, an Aspergillus isolated from an algae sample collected near the island of Gozo in the Mediterranean Sea. Bioactivity-guided fractionation of the crude fungal extract by column chromatography and high-performance liquid chromatography led to the isolation of several candidate compounds. Structure elucidation and identification of these molecules was mainly done by 1- and 2-dimensional nuclear magnetic resonance spectroscopy and mass spectrometry supported by natural products databases. Here I present the structures of the isolated compounds from Aspergillus sp. GOZO23y as well as detailed results from the antibacterial screening

Student Citizens: Whiteness, Inequality, and Social Reproduction in Marketized Music Education

Music education policy and administration attempts to shape the musical sensibilities of young people. Yet the logics of music education from a socioeconomic standpoint are inadequately understood. This dissertation focuses on the relationship between music education nonprofits and public schools and on the public and private policies that have shaped the formation and perpetuation of these relationships. I analyze the logics of policy documents alongside the discourses and narratives of private organizations that support music education within the specific contexts of New Jersey, a state that mandates music education access for all students, and the COVID-19 pandemic, which has exacerbated societal inequalities, to illuminate how policy makers and administrators shape student experiences in the proto-democratic space of the classroom. I use policy analysis and institutional ethnography, approaching data primarily through the lenses of neoliberal critiques of marketization, critical whiteness studies, and analyses of the intersection of class and race, which I outline in chapter one. I also consider the design of music education programs within the theoretical framework of culturally relevant pedagogy. Education systems are adapting to shifting racial discourses as schools continue to construct citizens within racialized and classed hierarchies. Music historically has been invoked in the construction of societal stratifications to mark ethnic and cultural boundaries. In chapter two, I examine these narratives that have shaped the formation of music education in the United States as a culturally hegemonizing force and persist in debates around the purpose of music education in under-resourced schools that mainly serve students from minoritized communities. Music education remains a site at which policy makers, administrators, educators, and community members negotiate the role of culture in shaping new citizens. State music education policy in New Jersey specifically struggles to support the progressive vision it professes as it continues to suggest a strongly hegemonic curriculum and perpetually underfunds music programs in schools. Within this context, the third chapter considers how funders and advocacy groups are so frequently focused on short-term funding needs that they persistently struggle to address systemic issues in music education, such as issues with administrations that do not represent the communities being served, colonial content and pedagogy, and unsustainable funding solutions. As such, the limited services and non-democratic leadership of privately funded music education programs in public schools reinforce the role of public schools as gate-keepers of exclusionary citizenship norms. At the same time, privatization has also opened opportunities for non-normative, anti-oppressive forms of music pedagogy to enter public schools. In the fourth chapter, I investigate how, though their very existence reinforces the marketizing trends that rank and exclude, some nonprofits do attempt to serve students in culturally relevant ways within this environment, and can even work in ways that support publicly funded programs. Altogether, my research provides insight into the role that the privatization of public spaces within neoliberalism plays in the formation and reproduction of classed and raced citizens, as policy makers, funders, and program administrators determine which young people are given access to which forms of education

On the Performance of the \u3ci\u3el\u3csub\u3eZ\u3c/sub\u3e\u3c/i\u3e Person-Fit Statistic

Person-fit measurement refers to statistical methods used to detect improbable item-score patterns. This study investigates the detection effectiveness of the z l statistic, which is one of the most popular and powerful person-fit statistics in the literature to date. The contributions of the present study are three-fold. First, the simulation results show that the detection power of the z l statistic is largely hinged on test characteristics, particularly the test difficulty. Therefore, the z l statistic should be used with caution in an operational testing environment. Second, this paper provides a clear explanation for the poor performance of the z l statistic under certain situations. The third objective is to present a summary of the patterns and conditions for which the z l statistic is not recommended for the detection of aberrancy. This can be used as a checklist for implementation purposes. Accessed 41,380 times on https://pareonline.net from December 05, 2007 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Nonparametric Double EWMA Control Chart for Process Monitoring

In monitoring process parameters, we assume normality of the quality characteristic of interest, which is an ideal assumption. In many practical situations, we may not know the distributional behavior of the data, and hence, the need arises use nonparametric techniques. In this study, a nonparametric double EWMA control chart, namely the NPDEWMA chart, is proposed to ensure efficient monitoring of the location parameter. The performance of the proposed chart is evaluated in terms of different run length properties, such as average, standard deviation and percentiles. The proposed scheme is compared with its recent existing counterparts, namely the nonparametric EWMA and the nonparametric CUSUM schemes. The performance measures used are the average run length (ARL), standard deviation of the run length (SDRL) and extra quadratic loss (EQL). We observed that the proposed chart outperforms the said existing schemes to detect shifts in the process mean level. We also provide an illustrative example for practical considerations.En el seguimiento de los parámetros del proceso, asumimos normalidadde la característica de calidad de interés que es un supuesto ideal. En muchas situaciones prácticas, no podemos conocer el comportamiento de distribución de los datos y por lo tanto, surge la necesidad de técnicas no paramétricas. En este estudio, un gráfico de control EWMA doble paramétrico, a saber, la carta NPDEWMA, se propone para una vigilancia eficaz en el parámetro de localización. El rendimiento del gráfico propuesto se evalúa en términos de propiedades diferentes de longitud de ejecución, como promedio, desviación estándar y percentiles. El esquema propuesto se compara con sus homólogos de los últimos existentes, a saber, la EWMA no paramétrico y los esquemas de CUSUM no paramétricas. Las medidas de desempeño utilizadas son la longitud promedio de carreras (ARL), la desviación estándar de la longitud de ejecución (SDRL) y pérdida cuadrática extra (EQL). Se observa que el gráfico propuesto supera a dichos regímenes existentes para detectar cambios en el proceso de nivel medio. También se proporciona un ejemplo ilustrativo para consideraciones prácticas

Earnings announcement return extrapolation

We propose that extrapolative beliefs about earnings announcement (EA) returns may contribute to our understanding of EA return patterns. We construct a theoretically-motivated measure of extrapolative investors’ expectations based on a stock’s recent history of EA returns. We then show that this measure explains cross-sectional variation in stock returns and investor behavior around EAs. Stocks expected to have high EA returns according to our measure experience predictable increases in prices before EAs and predictable decreases afterwards. These patterns are economically significant: investors that buy (sell) a portfolio that is long firms with high recent EA returns and short firms with low recent EA returns in the pre-EA (post-EA) period earn daily five-factor abnormal returns of 16.1 bps (18.3 bps). Using individual investor trades data and a measure of institutional trading, we find that individual and institutional investors are more likely to purchase stocks with high recent EA returns, consistent with at least a subset of investors forming extrapolative beliefs about EA returns

Guaranteed Conditional Performance of Control Charts via Bootstrap Methods

To use control charts in practice, the in-control state usually has to be estimated. This estimation has a detrimental effect on the performance of control charts, which is often measured for example by the false alarm probability or the average run length. We suggest an adjustment of the monitoring schemes to overcome these problems. It guarantees, with a certain probability, a conditional performance given the estimated in-control state. The suggested method is based on bootstrapping the data used to estimate the in-control state. The method applies to different types of control charts, and also works with charts based on regression models, survival models, etc. If a nonparametric bootstrap is used, the method is robust to model errors. We show large sample properties of the adjustment. The usefulness of our approach is demonstrated through simulation studies.Comment: 21 pages, 5 figure