Properties of macroeconomic forecast errors

This paper investigates the distributional properties of individual and consensus time series macroeconomic forecast errors, using data from the Survey of Professional Forecasters. The degree of autocorrelation and the presence of ARCH in the consensus errors is also determined. We find strong evidence of leptokurtic forecast errors and some evidence of skewness, suggesting that an assumption of error normality is inappropriate; many of the forecast error series are found to have non-zero mean, and we find sporadic evidence of consensus error ARCH. Properties of the distribution of cross-sectional forecast errors are also examined

Seasonal unit root tests with seasonal mean shifts

This paper analyses additive outlier and innovational outlier tests for seasonal unit roots when seasonal mean shifts occur under the null hypothesis. When the magnitude of the breaks is large, simulation evidence reveals that, for three of the four testing procedures considered, the endogenously determined break point can be incorrectly estimated, resulting in spurious rejections of the null. A simple modification to one of the testing approaches is proposed which achieves a substantial improvement in test size

Additional file 1: of A randomised, placebo-controlled trial of anti–interleukin-1 receptor 1 monoclonal antibody MEDI8968 in chronic obstructive pulmonary disease

Methods and Results relating to this manuscript. (DOCX 774 kb

Biological exacerbation clusters demonstrate asthma and COPD overlap with distinct mediator and microbiome profiles.

BACKGROUND: Exacerbations of asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous. OBJECTIVE: We sought to investigate the sputum cellular, mediator, and microbiome profiles of both asthma and COPD exacerbations. METHODS: Patients with severe asthma or moderate-to-severe COPD were prospectively recruited to a single centre. Sputum mediators were available in 32 asthma and 73 COPD patients assessed at exacerbation. Biologic clusters were determined using factor and cluster analyses on a panel of sputum mediators. Patterns of clinical parameters, sputum mediators, and microbiome communities were assessed across the identified clusters. RESULTS: The asthma and COPD patients had different clinical characteristics and inflammatory profiles, but similar microbial ecology. Three exacerbation biologic clusters were identified. Cluster 1 was COPD predominant, with 27 COPD and 7 asthma patients exhibiting elevated blood and sputum neutrophil counts, proinflammatory mediators (IL-1β, IL-6, IL-6R, TNFα, TNF-R1, TNF-R2, and VEGF), and proportion of the bacterial phylum Proteobacteria. Cluster 2 had 10 asthma and 17 COPD patients with elevated blood and sputum eosinophil counts, Type 2 (T2) mediators (IL-5, IL-13, CCL13, CCL17, and CCL26), and proportion of the bacterial phylum Bacteroidetes. Cluster 3 had 15 asthma and 29 COPD subjects with elevated Type 1 (T1) mediators (CXCL10, CXCL11, and IFN-ϒ) and proportions of phyla Actinobacteria and Firmicutes. CONCLUSIONS: A biologic clustering approach revealed three subgroups of asthma and COPD exacerbations each with different percentages of overlapping asthma and COPD patients. The sputum mediator and microbiome profiles were distinct between clusters. CLINICAL IMPLICATIONS: Sputum mediator and microbiome profiling can determine the distinct and overlapping asthma and COPD biologic exacerbation clusters, highlighting the heterogeneity of these exacerbations