FDI Determination and Corporate Tax Competition in a Volatile World

This paper investigates the role of economic and political volatility in the process of corporate tax-rate determination. The article is based on a theoretical framework that allows for the ability of multinational firms to choose the optimal timing of foreign investment and to shift profits by transfer pricing, and provides an empirical analysis on a large panel data set of countries over the 1983-2003 period. First, a reduced-form dynamic equation of corporate tax rate determination is estimated by the generalised method of moments (GMM), where a country’s top statutory corporate tax rate depends on a number of measures of economic and political volatility. The fundamental testable prediction derived from the theoretical model is that increased volatility should reduce a country’s corporate tax rate. Our results support the hypothesis that economic volatility is associated with lower top statutory corporate tax rates, while our measures of political volatility have no significant impact on corporate taxation policy. In order to identify the channels through which volatility works, we also estimate a structural model allowing for simultaneous determination of the corporate tax rate and the inflow of FDI to a particular country. The estimates of the structural model show that economic volatility affects the corporate tax setting process through their impact on FDI inflow.foreign direct investment, tax competition, volatility

Performance specifications for measurement uncertainty of common biochemical measurands according to Milan models.

Abstract Objectives Definition and fullfillment of analytical performance specifications (APS) for measurement uncertainty (MU) allow to make laboratory determinations clinically usable. The 2014 Milan Strategic Conference have proposed models to objectively derive APS based on: (a) the effect of analytical performance on clinical outcome; (b) biological variation components; and (3) the state of the art of the measurement, defined as the highest level of analytical performance technically achievable. Using these models appropriately, we present here a proposal for defining APS for standard MU for some common biochemical measurands. Methods We allocated a group of 13 measurands selected among the most commonly laboratory requested tests to each of the three Milan models on the basis of their biological and clinical characteristics. Both minimum and desirable levels of quality of APS for standard MU of clinical samples were defined by using information obtained from available studies. Results Blood total hemoglobin, plasma glucose, blood glycated hemoglobin, and serum 25-hydroxyvitamin D3 were allocated to the model 1 and the corresponding desirable APS were 2.80, 2.00, 3.00, and 10.0%, respectively. Plasma potassium, sodium, chloride, total calcium, alanine aminotransferase, creatinine, urea, and total bilirubin were allocated to the model 2 and the corresponding desirable APS were 1.96, 0.27, 0.49, 0.91, 4.65, 2.20, 7.05, and 10.5%, respectively. For C-reactive protein, allocated to the model 3, a desirable MU of 3.76% was defined. Conclusions APS for MU of clinical samples derived in this study are essential to objectively evaluate the reliability of results provided by medical laboratories

Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference

Measurements in clinical laboratories produce results needed in the diagnosis and monitoring of patients. These results are always characterized by some uncertainty. What quality is needed and what measurement errors can be tolerated without jeopardizing patient safety should therefore be defined and specified for each analyte having clinical use. When these specifications are defined, the total examination process will be "fit for purpose" and the laboratory professionals should then set up rules to control the measuring systems to ensure they perform within specifications. The laboratory community has used different models to set performance specifications (PS). Recently, it was felt that there was a need to revisit different models and, at the same time, to emphasize the presuppositions for using the different models. Therefore, in 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) organized a Strategic Conference in Milan. It was felt that there was a need for more detailed discussions on, for instance, PS for EQAS, which measurands should use which models to set PS and how to set PS for the extra-analytical phases. There was also a need to critically evaluate the quality of data on biological variation studies and further discussing the use of the total error (TE) concept. Consequently, EFLM established five Task Finish Groups (TFGs) to address each of these topics. The TFGs are finishing their activity on 2017 and the content of this paper includes deliverables from these groups

Defining a roadmap for harmonizing quality indicators in Laboratory Medicine: A consensus statement on behalf of the IFCC Working Group "laboratory Error and Patient Safety" and EFLM Task and Finish Group "performance specifications for the extra-analytical phases"

The improving quality of laboratory testing requires a deep understanding of the many vulnerable steps involved in the total examination process (TEP), along with the identification of a hierarchy of risks and challenges that need to be addressed. From this perspective, the Working Group \u201cLaboratory Errors and Patient Safety\u201d (WG-LEPS) of International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) is focusing its activity on implementation of an efficient tool for obtaining meaningful information on the risk of errors developing throughout the TEP, and for establishing reliable information about error frequencies and their distribution. More recently, the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has created the Task and Finish Group \u201cPerformance specifications for the extraanalytical phases\u201d (TFG-PSEP) for defining performance specifications for extra-analytical phases. Both the IFCC and EFLM groups are working to provide laboratories with a system to evaluate their performances and recognize the critical aspects where improvement actions are needed. A Consensus Conference was organized in Padova, Italy, in 2016 in order to bring together all the experts and interested parties to achieve a consensus for effective harmonization of quality indicators (QIs). A general agreement was achieved and the main outcomes have been the release of a new version of model of quality indicators (MQI), the approval of a criterion for establishing performance specifications and the definition of the type of information that should be provided within the report to the clinical laboratories participating to the QIs project

Defining a roadmap for harmonizing quality indicators in Laboratory Medicine: A consensus statement on behalf of the IFCC Working Group "laboratory Error and Patient Safety" and EFLM Task and Finish Group "performance specifications for the extra-analytical phases"

The improving quality of laboratory testing requires a deep understanding of the many vulnerable steps involved in the total examination process (TEP), along with the identification of a hierarchy of risks and challenges that need to be addressed. From this perspective, the Working Group “Laboratory Errors and Patient Safety” (WG-LEPS) of International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) is focusing its activity on implementation of an efficient tool for obtaining meaningful information on the risk of errors developing throughout the TEP, and for establishing reliable information about error frequencies and their distribution. More recently, the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has created the Task and Finish Group “Performance specifications for the extraanalytical phases” (TFG-PSEP) for defining performance specifications for extra-analytical phases. Both the IFCC and EFLM groups are working to provide laboratories with a system to evaluate their performances and recognize the critical aspects where improvement actions are needed. A Consensus Conference was organized in Padova, Italy, in 2016 in order to bring together all the experts and interested parties to achieve a consensus for effective harmonization of quality indicators (QIs). A general agreement was achieved and the main outcomes have been the release of a new version of model of quality indicators (MQI), the approval of a criterion for establishing performance specifications and the definition of the type of information that should be provided within the report to the clinical laboratories participating to the QIs project

Multicenter Evaluation of the TOSOH AIA-Pack Second-Generation Cardiac Troponin I Assay

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Definition of the Immune Parameters Related to COVID-19 Severity

A relevant portion of patients with disease caused by the severe acute respiratory syndrome coronavirus 2 (COVID-19) experience negative outcome, and several laboratory tests have been proposed to predict disease severity. Among others, dramatic changes in peripheral blood cells have been described. We developed and validated a laboratory score solely based on blood cell parameters to predict survival in hospitalized COVID-19 patients. We retrospectively analyzed 1,619 blood cell count from 226 consecutively hospitalized COVID-19 patients to select parameters for inclusion in a laboratory score predicting severity of disease and survival. The score was derived from lymphocyte- and granulocyte-associated parameters and validated on a separate cohort of 140 consecutive COVID-19 patients. Using ROC curve analysis, a best cutoff for score of 30.6 was derived, which was associated to an overall 82.0% sensitivity (95% CI: 78–84) and 82.5% specificity (95% CI: 80–84) for detecting outcome. The scoring trend effectively separated survivor and non-survivor groups, starting 2 weeks before the end of the hospitalization period. Patients’ score time points were also classified into mild, moderate, severe, and critical according to the symptomatic oxygen therapy administered. Fluctuations of the score should be recorded to highlight a favorable or unfortunate trend of the disease. The predictive score was found to reflect and anticipate the disease gravity, defined by the type of the oxygen support used, giving a proof of its clinical relevance. It offers a fast and reliable tool for supporting clinical decisions and, most important, triage in terms of not only prioritization but also allocation of limited medical resources, especially in the period when therapies are still symptomatic and many are under development. In fact, a prolonged and progressive increase of the score can suggest impaired chances of survival and/or an urgent need for intensive care unit admission

Laboratory testing in the emergency department: an Italian Society of Clinical Biochemistry and Clinical Molecular Biology (SIBioC) and Academy of Emergency Medicine and Care (AcEMC) consensus report

The mainstay of patient-oriented laboratory testing in emergency settings entails selecting number and type of tests according to valid criteria of appropriateness. Since the pattern of urgent tests requesting is variable across different institutions, we designed a joined survey between the Academy of Emergency Medicine and Care (AcEMC) and the Italian Society of Clinical Biochemistry and Clinical Molecular Biology (SIBioC) for reaching tentative consensus about the most informative diagnostic tests in emergency settings. A survey, containing the most commonly performed urgent laboratory tests and the relative clinical indications, was disseminated to eight relevant members of AcEMC and eight relevant members of SIBioC. All contributors were asked to provide numerical scores for the different laboratory parameters, where 1 indicated strongly recommended, 2 recommended in specific circumstances, and 3 strongly discouraged. The mean results of the survey were presented as the mean of responders' values, and the parameters were finally classified as strongly recommended (mean value, 1.0-1.5), somehow recommended (mean value, 1.5-2.0), discouraged (mean value, 2.0-2.5) and strongly discouraged (mean value, 2.5-3.0). The results of the survey allowed defining a hierarchy of priority, wherein 24 tests were strongly recommended. The use of 5 common tests was instead strongly discouraged. For 16 additional parameters in the list, the consensus ranged between somehow recommended and discouraged. We hope that results presented in this joint AcEMC-SIBioC consensus document may help harmonizing panel of tests and requesting patters in emergency setting, at least at a national level

Multicenter Evaluation of a 0-Hour/1-Hour Algorithm in the Diagnosis of Myocardial Infarction With High-Sensitivity Cardiac Troponin T

Study objectiveWe aim to prospectively validate the diagnostic accuracy of the recently developed 0-h/1-h algorithm, using high-sensitivity cardiac troponin T (hs-cTnT) for the early rule-out and rule-in of acute myocardial infarction.MethodsWe enrolled patients presenting with suspected acute myocardial infarction and recent (<6 hours) onset of symptoms to the emergency department in a global multicenter diagnostic study. Hs-cTnT (Roche Diagnostics) and sensitive cardiac troponin I (Siemens Healthcare) were measured at presentation and after 1 hour, 2 hours, and 4 to 14 hours in a central laboratory. Patient triage according to the predefined hs-cTnT 0-hour/1-hour algorithm (hs-cTnT below 12 ng/L and Δ1 hour below 3 ng/L to rule out; hs-cTnT at least 52 ng/L or Δ1 hour at least 5 ng/L to rule in; remaining patients to the “observational zone”) was compared against a centrally adjudicated final diagnosis by 2 independent cardiologists (reference standard). The final diagnosis was based on all available information, including coronary angiography and echocardiography results, follow-up data, and serial measurements of sensitive cardiac troponin I, whereas adjudicators remained blinded to hs-cTnT.ResultsAmong 1,282 patients enrolled, acute myocardial infarction was the final diagnosis for 213 (16.6%) patients. Applying the hs-cTnT 0-hour/1-hour algorithm, 813 (63.4%) patients were classified as rule out, 184 (14.4%) were classified as rule in, and 285 (22.2%) were triaged to the observational zone. This resulted in a negative predictive value and sensitivity for acute myocardial infarction of 99.1% (95% confidence interval [CI] 98.2% to 99.7%) and 96.7% (95% CI 93.4% to 98.7%) in the rule-out zone (7 patients with false-negative results), a positive predictive value and specificity for acute myocardial infarction of 77.2% (95% CI 70.4% to 83.0%) and 96.1% (95% CI 94.7% to 97.2%) in the rule-in zone, and a prevalence of acute myocardial infarction of 22.5% in the observational zone.ConclusionThe hs-cTnT 0-hour/1-hour algorithm performs well for early rule-out and rule-in of acute myocardial infarction