Information flows among rivals and corporate investment

Using a novel pairwise measure of firms' acquisitions of rivals' disclosures, we show that investment opportunities drive interfirm information flows. We find that these flows predict subsequent mergers and acquisitions as well as how and how much firms invest, relative to rivals. Moreover, firms' use of rivals' information often hinges on the similarities of their products. Our results suggest that rivals' public information, far from being unusable, helps facilitate investment and product decisions, including acquisitions and product differentiation strategies. The findings also support a learning mechanism that could partly underlie the emerging literature on peer investment effects

Survey of attitudes toward performing and reflecting on required team service-learning (SASL): psychometric data and reliability/validity for healthcare professions students in preclinical courses

PurposePreviously we assessed healthcare professional students’ feelings about team-based learning, implicit bias, and service to the community using an in-house paper survey. In this study, we determined whether this survey is a reliable and valid measure of prospective medical students’ attitudes toward required service-learning in an Immunology course. To our knowledge, no published questionnaire has been shown to be dependable and useful for measuring such attitudes using only eight survey items.MethodsFifty-eight prospective medical students in Colorado (CO) and 15 in Utah (UT) completed the same Immunology course using remote technology. In addition to the usual course content, students were required to write critical reflections on required team service-learning. On the last day of class, they completed the survey of attitudes toward service-learning (SASL).ResultsData analyses found Cronbach’s alpha values of 0.84 and 0.85 for the surveys of UT and CO students, respectively. Factor analysis of CO student data revealed only one Eigenvalue greater than one (3.95) justifying retention of a single factor termed “attitudes toward required service-learning.” In addition, CO students’ attitudes toward community service were highly positive, while UT students’ attitudes were nearer neutral (p < 0.0001).ConclusionOur factor analysis and good Cronbach’s alpha values support the conclusion that the SASL was a reliable measure of prospective medical students’ attitudes toward required team service-learning for an Immunology course. Moreover, we used the SASL to distinguish these attitudes in CO versus UT students, and, thus, the SASL appears to be a valid measure of this difference. Calculation of similarly good Cronbach’s alpha values – for a predecessor of the SASL among pharmacy, masters, and medical students at another institution – indicates that the SASL may be useful more widely. However, the reliability and validity of the SASL needs to be demonstrated more rigorously for other healthcare students at different universities

An examination of firms’ responses to tax forgiveness

This study uses state tax amnesties to examine how firms respond to forgiveness—particularly repeated forgiveness—by a taxing authority. We posit that tax forgiveness programs alter taxpayer perceptions of the probability of detection by enforcers or the probability of future forgiveness programs, either of which could affect future tax aggressiveness. We find that firms headquartered in an amnesty-granting state increase state income tax aggressiveness following the first instance of tax amnesty, relative to control firms in other states. Moreover, we find evidence that tax aggressiveness incrementally increases with each additional repetition of a tax amnesty. Finally, we find that the effect of amnesties on tax aggressiveness is more prominent for small firms, which face less scrutiny and for which the tax aggressiveness measures are less confounded. Our findings suggest that repeated programs of tax forgiveness have increasingly negative implications for corporate tax collections

Data informed multipoint ground flare evaluation using measurement and theory

reportThis paper will explore the comparison of experimental (PFTIR) and simulation data obtained from assisted multipoint ground flares operating at high turndown. The flare assist is intended to encourage air entrainment for best combustion efficiency as well as reduce visible smoke. Operational envelopes of the assist to vent gas ratios are regulated on flare specific parameters. Experimental measurements have, however, measured low combustion efficiency even when operating within flare regulatory guidelines. This result is most likely due to the nonlinear nature of the flare combustion process and its response to regulatory constraints while being exposed to chaotic environmental conditions. Reliable and accurate methods for measuring, predicting and controlling flare performance across a wide range of conditions could offer significant environmental and economical advantages through better informed regulation, operation and ultimately high combustion efficiency. PFTIR measurements represent a promising technology for remote flare sensing, as they may be placed safely away from the combustion zone and report critical species concentrations along a line of sight from which a combustion efficiency may be computed. However, environmental conditions, experimental error and bias significantly affect the measured combustion efficiency. Advanced simulation techniques have also offered a promising avenue for evaluating flare performance. However, these simulation tools may require large computational resources or require high level expertise to run and evaluate. While both the experimental and simulation approach have their limitations, the combination of the two data sources can offer significant insight into the flare's performance and even offer realtime feedback for operation and control

An examination of firms’ responses to tax forgiveness

This study uses state tax amnesties to examine how firms respond to forgiveness—particularly repeated forgiveness—by a taxing authority. We posit that tax forgiveness programs alter taxpayer perceptions of the probability of detection by enforcers or the probability of future forgiveness programs, either of which could affect future tax aggressiveness. We find that firms headquartered in an amnesty-granting state increase state income tax aggressiveness following the first instance of tax amnesty, relative to control firms in other states. Moreover, we find evidence that tax aggressiveness incrementally increases with each additional repetition of a tax amnesty. Finally, we find that the effect of amnesties on tax aggressiveness is more prominent for small firms, which face less scrutiny and for which the tax aggressiveness measures are less confounded. Our findings suggest that repeated programs of tax forgiveness have increasingly negative implications for corporate tax collections

Facilitating Level Three Cache Studies Using Set Sampling

We discuss some of the difficulties present in trace collection and trace-driven cache simulation. We then describe our multiprocessor tracing technique and verify that it accurately collects long traces. We propose sampling as a method to reduce required disk space, enable simulations to run faster, and effectively enlarge the trace buffer of our hardware monitor, decreasing trace distortion. To this end, we investigate time sampling and two types of set sampling. We conclude that the second set sampling technique achieves the most accurate results. The miss rate for the second set sampling method is calculated as the number of misses to sampled sets divided by the total number of references scaled by the sample size. We determined that a 10% sample size was the most accurate while still reducing required disk space