Forecasting recessions using the yield curve

We compare forecasts of recessions using four different specifications of the probit model: a time invariant conditionally independent version; a business cycle specific conditionally independent model; a time invariant probit with autocorrelated errors; and a business cycle specific probit with autocorrelated errors. The more sophisticated versions of the model take into account some of the potential underlying causes of the documented predictive instability of the yield curve. We find strong evidence in favour of the more sophisticated specification, which allows for multiple breakpoints across business cycles and autocorrelation. We also develop a new approach to the construction of real time forecasting of recession probabilities. Copyright © 2005 John Wiley & Sons, Ltd.     

Are forecasters reluctant to revise their predictions? Some German evidence

People are reluctant to admit mistakes. This could also be true of economic forecasters. If revisions of past forecasts are costly, then it will become optimal for forecasters to only partially adjust a past forecast in the light of new information. The unwillingness to admit to the mistake in the old forecast generates a bias of the new forecast in the direction of the old forecast. We test this hypothesis for the joint predictions of the Association of German Economic Research Institutes over the last 35 years. We find some evidence for such a bias and compute the implied unwillingness to revise forecasts. Copyright © 2006 John Wiley & Sons, Ltd.     

A hybrid forecasting approach for piece‐wise stationary time series

We consider the problem of forecasting a stationary time series when there is an unknown mean break close to the forecast origin. Based on the intercept‐correction methods suggested by Clements and Hendry (1998) and Bewley (2003), a hybrid approach is introduced, where the break and break point are treated in a Bayesian fashion. The hyperparameters of the priors are determined by maximizing the marginal density of the data. The distributions of the proposed forecasts are derived. Different intercept‐correction methods are compared using simulation experiments. Our hybrid approach compares favorably with both the uncorrected and the intercept‐corrected forecasts. Copyright © 2006 John Wiley & Sons, Ltd.     

A ground‐level ozone forecasting model for Santiago,Chile

A physically based model for ground‐level ozone forecasting is evaluated for Santiago, Chile. The model predicts the daily peak ozone concentration, with the daily rise of air temperature as input variable; weekends and rainy days appear as interventions. This model was used to analyse historical data, using the Linear Transfer Function/Finite Impulse Response (LTF/FIR) formalism; the Simultaneous Transfer Function (STF) method was used to analyse several monitoring stations together. Model evaluation showed a good forecasting performance across stations—for low and high ozone impacts—with power of detection (POD) values between 70 and 100%, Heidke's Skill Scores between 40% and 70% and low false alarm rates (FAR). The model consistently outperforms a pure persistence forecast. Model performance was not sensitive to different implementation options. The model performance degrades for two‐ and three‐days ahead forecast, but is still acceptable for the purpose of developing an environmental warning system at Santiago. Copyright © 2002 John Wiley & Sons, Ltd.     

Forecasting trend output in the Euro area

This paper is an applied study about forecasting trend output and the output gap in the Euro area. The need for trend output forecasts is justified by an analysis of the monetary strategy of the European Central Bank. Trend output serves as a direct inflation indicator and helps to determine the reference value for money. For both purposes, trend output has to be forecasted. A permanent–transitory decomposition based on cointegration restrictions gives an estimate of trend output in the Euro area. Ex‐ante point forecasts of trend output are computed and bootstrap simulation is employed to construct prediction intervals that take estimation uncertainty into consideration. The uncertainty of trend output and the output gap is quite large and raises questions about their usefulness as indicators for monetary policy. Copyright © 2002 John Wiley & Sons, Ltd.     

沙漠绿洲区春小麦需水量及需水规律探讨

通过武威地区多站点,多年份,多种方法的灌溉试验成果,阐述了沙漠绿洲区春小区生育期间的需水量及需水规律,并对需水量与其相关因素的关系,需水量预测预报进行了分析论述,为灌溉管理和规划设计提供了科学依据。     

柘溪水库月入库流量预报方案的建立与对比分析

利用相关分析方法,对柘溪水库月入库流量与全球海温及27类气象因子的关系进行了分析研究．通过逐步回归,建立了3种类型的月入库流量预报模型,并进行了对比分析．研究结果表明：影响柘溪水库月径流量的主要因子有青藏高原西部西风带系统、西太平洋副热带高压和西南季风;前期海温对柘溪入库流量有重要影响,关键海区在北部印度洋和北赤道中西段．建议不同月份的预报可采用不同的预报模型,以期达到最好的效果．     

基于时间序列分析的桥梁长期挠度分离与预测

针对挠度长期监测信号的多尺度特性及温度荷载下挠度周期性变化的特点,利用修正平均周期图法获取信号分量周期长度,结合基于中心移动平均法的挠度温度效应分离策略,提取结构变形特征,运用ARIMA模型建立结构变形趋势的预测模型.以黄冈长江大桥为例,讨论了温度与挠度的相关性,通过模拟数值试验验证分离算法的有效性.实测数据的处理与分析结果表明,本文方法具有较高的可靠性和精度,可为桥梁进行损伤识别提供数据支持.     

陷落柱对W矿3#煤层底板破坏和隔水性能的影响

为了评估陷落柱对煤层底板的危害,运用数值模拟对所选取的W矿3#煤层进行了分析。根据柱状图,建立了一种计算模型,采用RFPA2D模拟了采场推进时煤层底板的破坏情况,估算了底板破坏深度。结果表明：随着回采工作面的推进,矿压和水压造成的顶板的破坏高度逐渐增加;工作面推进到150 m前,覆岩破坏没有发展到关键层1;随着回采工作面的推进,矿压和水压造成的底板的破坏深度也逐渐增大,工作面推进到135 m时,底板的破坏深度不再发生明显的变化,此时底板破坏深度大约16 m。工作面推进到150 m时,泥岩层尚未贯穿,成为隔水关键层,底板不受含水层的影响。另外,研究表明：贯穿煤层和达到煤层的陷落柱对底板破坏的影响比未达到煤层的陷落柱对底板破坏的影响大。     

区域土壤墒情模型研究

运用平原水文模型,参考不同作物不同生长期蒸散发特点及土层结构和土层蓄水量与土壤墒情之间的关系,构建区域土壤墒情模型,并利用山西省洪洞县实测土壤墒情资料对该模型进行了检验,检验结果表明,模型物理概念明确,可连续模拟或预报区域土壤墒情,且预报精度高。