The impact of exogenous shocks on the dynamics and persistence of inflation: a macroeconomic model-based approach for Greece

The paper analyses the dynamic response of inflation to various economic shocks and investigates the sources of inflation persistence through a set of counter factual simulations. Analysis shows that inflation seems to be more persistent in Greece than, on average, in Euro Area. Inflation persistence tends to be higher in response to fiscal shocks than others shocks. Only an indirect tax shock could be classified as “non-persistent” for Greece. Inflation persistence is crucially affected by the degree of competition in product market and it is mainly of intrinsic nature while nominal rigidities and frictions in the labor market do not seem important in explaining the relatively higher persistence of Greek inflation.Inflation persistence,macroeconomic models,impulse response function

A Nation Deceived: How Schools Hold Back America's Brightest Students, Volume II

Provides a comprehensive review of research on the academic acceleration of gifted students

Impact of infection preventionists on Centers for Medicare and Medicaid quality measures in Maryland nursing homes.

BackgroundHealth care-associated infections are the leading cause of morbidity and mortality in US nursing homes (NHs). The objective of the research is to assess the impact of Maryland NH infection preventionists (IPs) on NH quality measures.MethodsTwo hundred thirty-four NHs were queried through mailed survey. These survey data were then linked with 2008 quality data from Nursing Home Compare and the On-line Survey Certification of Automated Records.ResultsThree of the 8 quality measures examined-influenza vaccination for both short- and long-stay residents and pressure ulcer prevention in high-risk residents-were significantly associated with the number of IPs. None of the quality measures were shown to be significant with IPs who received specialized training on infection prevention and management compared with those who did not receive specialized training.ConclusionIPs play a critical role in preventing and managing health care-associated infections in nursing homes, especially in the areas of influenza vaccination and pressure ulcer prevention among high-risk nursing home residents. Quality measures that reflect the effects of IP training may not have been elucidated yet. Further research is needed to support the IP role in order for policy to advocate for increased IP funding

Airline Schedule Recovery after Airport Closures: Empirical Evidence Since September 11th

Since the September 11, 2001 terrorist attacks, repeated airport closures due to potential security breaches have imposed substantial costs on travelers, airlines, and government agencies in terms of flight delays and cancellations. Using data from the year following September 11th, this study examines how airlines recover flight schedules upon reopening of airports that have been closed for security reasons. As such, this is the first study to examine service quality during irregular operations. Our results indicate that while outcomes of flights scheduled during airport closures are difficult to explain, a variety of factors, including potential revenue per flight and logistical variables such as flight distance, seating capacity and shutdown severity, significantly predict outcomes of flights scheduled after airports reopen. Given the likelihood of continued security-related airport closings, understanding the factors that determine schedule recovery is potentially important.

Does School Choice Increase School Quality?

Federal No Child Left Behind' legislation, which enables students of low-performing schools to exercise public school choice, exemplies a widespread belief that competing for students will spur public schools to higher achievement. We investigate how the introduction of school choice in North Carolina, via a dramatic increase in the number of charter schools across the state, affects the performance of traditional public schools on statewide tests. We find test score gains from competition that are robust to a variety of specifications. The introduction of charter school competition causes an approximate one percent increase in the score, which constitutes about one quarter of the average yearly growth.

Deletion of Gpr27 in vivo reduces insulin mRNA but does not result in diabetes.

Gpr27 is a highly conserved, orphan G protein coupled receptor (GPCR) previously implicated in pancreatic beta cell insulin transcription and glucose-stimulated insulin secretion in vitro. Here, we characterize a whole-body mouse knockout of Gpr27. Gpr27 knockout mice were born at expected Mendelian ratios and exhibited no gross abnormalities. Insulin and Pdx1 mRNA in Gpr27 knockout islets were reduced by 30%, but this did not translate to a reduction in islet insulin content or beta cell mass. Gpr27 knockout mice exhibited slightly worsened glucose tolerance with lower plasma insulin levels while maintaining similar insulin tolerance. Unexpectedly, Gpr27 deletion reduced expression of Eif4e3, a neighboring gene, likely by deleting transcription start sites on the anti-sense strand of the Gpr27 coding exon. Our data confirm that loss of Gpr27 reduces insulin mRNA in vivo but has only minor effects on glucose tolerance

Particle Learning and Smoothing

Particle learning (PL) provides state filtering, sequential parameter learning and smoothing in a general class of state space models. Our approach extends existing particle methods by incorporating the estimation of static parameters via a fully-adapted filter that utilizes conditional sufficient statistics for parameters and/or states as particles. State smoothing in the presence of parameter uncertainty is also solved as a by-product of PL. In a number of examples, we show that PL outperforms existing particle filtering alternatives and proves to be a competitor to MCMC.Comment: Published in at http://dx.doi.org/10.1214/10-STS325 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Particle Learning for General Mixtures

This paper develops particle learning (PL) methods for the estimation of general mixture models. The approach is distinguished from alternative particle filtering methods in two major ways. First, each iteration begins by resampling particles according to posterior predictive probability, leading to a more efficient set for propagation. Second, each particle tracks only the "essential state vector" thus leading to reduced dimensional inference. In addition, we describe how the approach will apply to more general mixture models of current interest in the literature; it is hoped that this will inspire a greater number of researchers to adopt sequential Monte Carlo methods for fitting their sophisticated mixture based models. Finally, we show that PL leads to straight forward tools for marginal likelihood calculation and posterior cluster allocation.Business Administratio