HAVE RATING AGENCIES BECOME MORE CONSERVATIVE? EVIDENCES

Beginning in 2008, rating agencies have loosen their rating criteria of Chinese corporate bond rating.  The change in rating standard remains statistically significant after considering the macroeconomic factors.  A lack of diversification in ratings and failure to rate through economic cycle are found. As for the factors that have impact on the rating, Bigger size, higher profitability and better solvency help increase the rating for a corporate bound issuer, while higher liquidity, and lower leverage do harm to the credit rating. Such discoveries are consistent with the consitions in US corporate debt market.  Our conclusion is robust after multicollinearity test and adding additional macroeconomic explanatory variables

Effects of vegetation restoration types on soil nutrients and soil erodibility regulated by slope positions on the Loess Plateau

Soil degradation is significantly increased driven by soil nutrient loss and soil erodibility, thus, hampering the sustainable development of the ecological environment and agricultural production. Vegetation restoration has been widely adopted to prevent soil degradation given its role in improving soil nutrients and soil erodibility. However, it is unclear which vegetation type has the best improving capacity from soil nutrient and soil erodibility perspectives. This study selected three vegetation restoration types of grasslands (GL), shrublands (SL), and forestlands (FL) along the five slope positions (i.e., top, upper, middle, lower, and foot slope), to investigate the effects of vegetation restoration types on soil nutrients and soil erodibility. All vegetation restoration types were restored for 20 years from croplands (CL). We used comprehensive soil nutrient index (CSNI) and comprehensive soil erodibility index (CSEI) formed by a weighted summation method to reflect the effect of vegetation restoration on the improving capacity of soil nutrient and erodibility. The results showed the vegetation types with the highest comprehensive soil quality index (CSQI) at the top, upper, middle, lower and foot slope were FL (1.92), FL (1.98), SL (2.15), FL (2.37) and GL (3.93), respectively. When only one vegetation type was considered on the entire slope, SL (0.59) and FL (0.59) had the highest CSNI, the SL had the lowest CSEI (0.34) and the highest CSQI (1.89). The CSNI was mainly influenced by soil structure stability index (SSSI), sand content, silt + clay particles, and CSEI was controlled by soil organic matter (SOM), macroaggregates and microaggregates. Moreover, the CSQI was influenced by pH, silt and clay content, and biome coverage (BC). The study suggested the SL were advised as the best vegetation restoration type on the whole slope from improving soil nutrients and soil erodibility

Are medical record front page data suitable for risk adjustment in hospital performance measurement? Development and validation of a risk model of in-hospital mortality after acute myocardial infarction

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement