Beating the VAR: Improving Swedish GDP Forecasts Using Error and Intercept Corrections

This paper examines the forecast accuracy of an unrestricted vector autoregressive (VAR) model for GDP, relative to a comparable vector error correction model (VECM) that recognizes that the data are characterized by co‐integration. In addition, an alternative forecast method, intercept correction, is considered for further comparison. Recursive out‐of‐sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VECM consistently outperforms the VAR models. Further, intercept correction enhances the forecast accuracy when applied to the VECM, whereas there is no such indication when applied to the VAR model. For certain forecast horizons there is a significant difference in forecast ability between the intercept corrected VECM compared to the VAR model. Copyright © 2015 John Wiley & Sons, Ltd.     

Prediction in context: On the comparative epistemic merit of predictive success

The considerations set out in the paper are intended to suggest that in practical contexts predictive power does not play the outstanding roles sometimes accredited to it in an epistemic framework. Rather, predictive power is part of a network of other merits and achievements. Predictive power needs to be judged differently according to the specific conditions that apply. First, predictions need to be part of an explanatory framework if they are supposed to guide actions reliably. Second, in scientific expertise, the demand for accurate predictions is replaced with the objective of specifying a robust corridor of estimates. Finally, it is highly uncertain to predict the success of research projects. The overall purpose of the paper is to enlarge the debate about predictions by addressing specifically the roles of predictions in application-oriented research.     

Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.     

基于稳态随机动力响应的蒙特卡洛模拟精度研究

以高斯白噪声作用下的单质点线性系统为例,探讨了系统稳态随机响应的蒙特卡洛模拟精度.结果表明,模拟的精度与样本数、样本值域分段数和系统参数的取值有关:样本数的选择应综合考虑计算精度与计算量,而合理选择分段数可以有效改善计算结果的精度.     

求解多尺度双曲型问题的一种新方法

建立了有限体积非均匀化多尺度方法（Finite Volume Heterogeneous Multi-scale Method,FV—HMM）,将其应用于二阶多尺度双曲型问题的求解。该方法分别在宏观尺度和细观尺度上建立原方程的差分格式。通过不同尺度间的耦合．有效地减小了计算所需代价。数值实验结果表明：FV—HMM比传统的有限体积法有效,既大大地节省了计算量,又有较高的精度。     

模糊综合评判法在高校教学评估中的应用

模糊综合评判法用于评估高等教育的原理在于要用模糊集合论及其隶属度。此种方法的优点在于：数学模型简单,易于应用和对多指标的复杂问题评估得到较好的结果。     

诉讼离婚背后的法律问题及司法建议

“80后”闪婚、闪离、逼婚的现象在社会中愈来愈常见，尤其是闪离事件的频发，引发了社会的广泛关注，在此过程中也出现了各种法律纠纷。本文立足于诉讼离婚案件，分析了诉讼离婚的现行标准及缺陷、离婚诉讼中缺席判决和公告送达的弊端，并且提出了离婚诉讼标准、诉讼离婚中缺席判决和公告送达的司法建议。     

影响机械加工精度的主要因素

文章介绍了影响机械加工精度的几个重要因素。在诸多误差因素中,机床的几何误差、工艺系统的受力变形和受热变形占有突出的位置,通过了解这些误差因素是如何影响加工误差的,可以使工件的加工达到质量要求。     

从精准性及模糊性特征论法律语言的翻译策略

一切法律规范都需要通过语言来表达,语言之外不存在法律.法律语言既具有精准性的特征,也具有模糊性的特征.从事法律语言翻译要在熟知法律语言双重特征的基础上遵循以下翻译策略：术语的一致性、句法的规范性、表意的等效性以及模糊度的对等性.     

Analysts’ Dynamic Decisions: Timeliness versus Accuracy

For analysts there is a tradeoff between the accuracy and the timeliness of their forecasts. Prior literature heavily investigates analyst forecast accuracy. Few papers investigate the importance of timeliness. To our best knowledge, there are no empirical papers to date to investigate the dynamic interplay between these key characteristics. We show that if analysts experience a period of high accuracy relative to their peers, they subsequently focus more on the timeliness of their forecasts in the subsequent period and thus issue their forecasts earlier than they did in the prior period. Copyright © 2016 John Wiley & Sons, Ltd.