In the present paper, we model the policy stance of the People's Bank of China (PBC) as a latent variable, and the discrete changes in the reserve requirement ratio, policy interest rates, and the scale of open market operations are taken as signals of movement of this latent variable. We run a discrete choice regression that relates these observed indicators of policy stance to major trends of macroeconomic and financial developments, which are represented by common factors extracted from a large number of variables. The predicted value of the estimated model can then be interpreted as the implicit policy stance of the PBC. In a second step, we estimate how much of the variation in the PBC's implicit stance can be explained by measures of its policy objectives on inflation, growth and financial stability. We find that deviations of CPI inflation from an implicit target and deviations of broad money growth from the announced targets, but not output gaps, figure significantly in the PBC's policy changes. Copyright (c) 2008 The Hong Kong Monetary Authority Journal compilation (c) 2008 Institute of World Economics and Politics, Chinese Academy of Social Sciences.

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This paper investigates whether external political pressure for faster renminbi (RMB) appreciation affect both the daily returns and the conditional volatility of the RMB central parity rate. We construct several political pressure indicators pertaining to the RMB exchange rate, with a special emphasis on the US pressure, to test the hypothesis. After controlling for Chinese macroeconomic surprise news, we find that US and non-US political pressure does not have a significant influence on RMB's daily returns. However, evidence suggests that political pressures, and especially those from the US, have statistically significant impacts on the conditional volatility of the RMB. Furthermore, we conduct the same exercise on the 12-month RMB nondeliverable forward rate (NDF). We find that the NDF market is highly responsive to macroeconomic surprise news and there is some evidence that Sino-US bilateral meetings affect the conditional volatility of the RMB NDF. Abstract This paper investigates whether external political pressure for faster renminbi (RMB) appreciation affect both the daily returns and the conditional volatility of the RMB central parity rate. We construct several political pressure indicators pertaining to the RMB exchange rate, with a special emphasis on the US pressure, to test the hypothesis. After controlling for Chinese macroeconomic surprise news, we find that US and non-US political pressure does not have a significant influence on RMB's daily returns. However, evidence suggests that political pressures, and especially those from the US, have statistically significant impacts on the conditional volatility of the RMB. Furthermore, we conduct the same exercise on the 12-month RMB non-deliverable forward rate (NDF). We find that the NDF market is highly responsive to macroeconomic surprise news and there is some evidence that Sino-US bilateral meetings affect the conditional volatility of the RMB NDF.

Introduction: Non-thyroidal illness (NTI), which occurs with fasting and in response to illness, is characterized by thyroid hormone inactivation with low triiodothyronine (T3) and high reverse T3 (rT3), followed by suppressed thyrotropin (TSH). Withholding supplemental parenteral nutrition early in pediatric critical illness (late-PN), thus accepting low/no macronutrient intake up to day 8 in the pediatric intensive care unit (PICU), accelerated recovery compared to initiating supplemental parenteral nutrition early (early-PN). Whether NTI is harmful or beneficial in pediatric critical illness and how it is affected by a macronutrient deficit remains unclear. This study investigated the prognostic value of NTI, the impact of late-PN on NTI, and whether such impact explains or counteracts the outcome benefit of late-PN in critically ill children. Methods: This preplanned secondary analysis of the Early versus Late Parenteral Nutrition in the Pediatric Intensive Care Unit randomized controlled trial quantified serum TSH, total thyroxine (T4), T3, and rT3 concentrations in 982 patients upon PICU admission versus 64 matched healthy children and in 772 propensity score-matched early-PN and late-PN patients upon admission and at day 3 or last PICU day for shorter PICU stay. Associations between thyroid hormone concentrations upon admission and outcome, as well as impact of late-PN on NTI in relation with outcome, were assessed with univariable analyses and multivariable logistic regression, linear regression, or Cox proportional hazard analysis, adjusted for baseline risk factors. Results: Upon PICU admission, critically ill children revealed lower TSH, T4, T3, and T3/rT3 and higher rT3 than healthy children ( p < 0.0001). A more pronounced NTI upon admission, with low T4, T3, and T3/rT3 and high rT3 was associated with higher mortality and morbidity. Late-PN further reduced T4, T3, and T3/rT3 and increased rT3 ( p £ 0.001). Statistically, the further lowering of T4 by late-PN reduced the outcome benefit ( p < 0.0001), whereas the further lowering of T3/rT3 explained part of the outcome benefit of late-PN ( p £ 0.004). This effect was greater for infants than for older children. Conclusion:In critically ill children, the peripheral inactivation of thyroid hormone, characterized by a decrease in T3/rT3, which is further accentuated by low/no macronutrient intake, appears beneficial. In contrast, the central component of NTI attributable to suppressed TSH, evidenced by the decrease in T4, seems to be a harmful response to critical illness. Whether treating the central component with TSH releasing hormone infusion in the PICU is beneficial requires further investigation.

This paper provides a methodology for combining forecasts based on several discrete choice models. This is achieved primarily by combining one-step-ahead probability forecast associated with each model. The paper applies well-established scoring rules for qualitative response models in the context of forecast combination. Log-scores and quadratic-scores are both used to evaluate the forecasting accuracy of each model and to combine the probability forecasts. In addition to producing point forecasts, the effect of sampling variation is also assessed. This methodology is applied to forecast the US Federal Open Market Committee (FOMC) decisions in changing the federal funds target rate. Several of the economic fundamentals influencing the FOMC decisions are nonstationary over time and are modelled in a similar fashion to Hu and Phillips (2004a, JoE). The empirical results show that combining forecasted probabilities using scores mostly outperforms both equal weight combination and forecasts based on multivariate models. Abstract This paper provides a methodology for combining forecasts based on several discrete choice models. This is achieved primarily by combining one-step-ahead probability forecast associated with each model. The paper applies well-established scoring rules for qualitative response models in the context of forecast combination. Log-scores and quadratic-scores are both used to evaluate the forecasting accuracy of each model and to combine the probability forecasts. In addition to producing point forecasts, the effect of sampling variation is also assessed. This methodology is applied to forecast the US Federal Open Market Committee (FOMC) decisions in changing the federal funds target rate. Several of the economic fundamentals influencing the FOMC decisions are nonstationary over time and are modelled in a similar fashion to Hu and Phillips (2004a, JoE). The empirical results show that combining forecasted probabilities using scores mostly outperforms both equal weight combination and forecasts based on multivariate models.