A lot, including a few things you may not expect. Previous studies find that the term spread forecasts GDP but these regressions are unconstrained and do not model regressor endogeneity. We build a dynamic model for GDP growth and yields that completely characterizes expectations of GDP. The model does not permit arbitrage. Contrary to previous findings, we predict that the short rate has more predictive power than any term spread. We confirm this finding by forecasting GDP out-ofsample. The model also recommends the use of lagged GDP and the longest maturity yield to measure slope. Greater efficiency enables the yield-curve model to produce superior out-of-sample GDP forecasts than unconstrained OLS regressions at all horizons.

Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several optimal methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts using means or medians, or using optimal weights with prior information produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.

Highlights d Cryo-EM structure of SARS-CoV-2 nsp12-nsp7-nsp8 core polymerase complex d The core complex of SARS-CoV-2 has lower enzymatic activity than SARS-CoV d SARS-CoV-2 nsp7-8-12 subunits are less thermostable than the SARS-CoV counterpart

Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several optimal methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts using means or medians, or using optimal weights with prior information produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.

A lot, including a few things you may not expect. Previous studies find that the term spread forecasts GDP but these regressions are unconstrained and do not model regressor endogeneity. We build a dynamic model for GDP growth and yields that completely characterizes expectations of GDP. The model does not permit arbitrage. Contrary to previous findings, we predict that the short rate has more predictive power than any term spread. We confirm this finding by forecasting GDP out-ofsample. The model also recommends the use of lagged GDP and the longest maturity yield to measure slope. Greater efficiency enables the yield-curve model to produce superior out-of-sample GDP forecasts than unconstrained OLS regressions at all horizons.

Allergic rhinitis (AR) is a global health problem that causes major illnesses and disabilities worldwide. Epidemiologic studies have demonstrated that the prevalence of AR has increased progressively over the last few decades in more developed countries and currently affects up to 40% of the population worldwide. Likewise, a rising trend of AR has also been observed over the last 2–3 decades in developing countries including China, with the prevalence of AR varying widely in these countries. A survey of self-reported AR over a 6-year period in the general Chinese adult population reported that the standardized prevalence of adult AR increased from 11.1% in 2005 to 17.6% in 2011. An increasing number of original articles and imporclinical trials on the epidemiology, pathophysiologic mechanisms, diagnosis, management and comorbidities of AR in Chinese subjects have been published in international peer-reviewed journals over the past 2 decades, and substantially added to our understanding of this disease as a global problem. Although guidelines for the diagnosis and treatment of AR in Chinese subjects have also been published, they have not been translated into English and therefore not generally accessible for reference to non-Chinese speaking international medical communities. Moreover, methods for the diagnosis and treatment of AR in China have not been standardized entirely and some patients are still treated according to regional preferences. Thus, the present guidelines have been developed by the Chinese Society of Allergy to be accessible to both national and international medical communities involved in the management of AR patients. These guidelines have been prepared in line with existing international guidelines to provide evidence-based recommendations for the diagnosis and management of AR in China.

Abstract. The main advancements of the Beijing Climate Center (BCC) climate system model from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to phase 6 (CMIP6) are presented, in terms of physical parameterizations and model performance. BCC-CSM1.1 and BCC-CSM1.1m are the two models involved in CMIP5, whereas BCC-CSM2-MR, BCC-CSM2-HR, and BCC-ESM1.0 are the three models configured for CMIP6. Historical simulations from 1851 to 2014 from BCC-CSM2-MR (CMIP6) and from 1851 to 2005 from BCC-CSM1.1m (CMIP5) are used for models assessment. The evaluation matrices include the following: (a) the energy budget at top-of-atmosphere; (b) surface air temperature, precipitation, and atmospheric circulation for the global and East Asia regions; (c) the sea surface temperature (SST) in the tropical Pacific; (d) sea-ice extent and thickness and Atlantic Meridional Overturning Circulation (AMOC); and (e) climate variations at different timescales, such as the global warming trend in the 20th century, the stratospheric quasi-biennial oscillation (QBO), the Madden–Julian Oscillation (MJO), and the diurnal cycle of precipitation. Compared with BCC-CSM1.1m, BCC-CSM2-MR shows significant improvements in many aspects including the tropospheric air temperature and circulation at global and regional scales in East Asia and climate variability at different timescales, such as the QBO, the MJO, the diurnal cycle of precipitation, interannual variations of SST in the equatorial Pacific, and the long-term trend of surface air temperature.

No abstract