Dynamic Model Averaging and CPI Inflation Forecasts: A Comparison between the Euro Area and the United States

The paper forecasts consumer price inflation in the euro area (EA) and in the USA between 1980:Q1 and 2012:Q4 based on a large set of predictors, with dynamic model averaging (DMA) and dynamic model selection (DMS). DMA/DMS allows not solely for coefficients to change over time, but also for changes in the entire forecasting model over time. DMA/DMS provides on average the best inflation forecasts with regard to alternative approaches (such as the random walk). DMS outperforms DMA. These results are robust for different sample periods and for various forecast horizons. The paper highlights common features between the USA and the EA. First, two groups of predictors forecast inflation: temporary fundamentals that have a frequent impact on inflation but only for short time periods; and persistent fundamentals whose switches are less frequent over time. Second, the importance of some variables (particularly international food commodity prices, house prices and oil prices) as predictors for consumer price index inflation increases when such variables experience large shocks. The paper also shows that significant differences prevail in the forecasting models between the USA and the EA. Such differences can be explained by the structure of these respective economies. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

How Informative are the Subjective Density Forecasts of Macroeconomists?

In this paper, we propose a framework to evaluate the subjective density forecasts of macroeconomists using micro data from the euro area Survey of Professional Forecasters (SPF). A key aspect of our analysis is the use of evaluation measures which take account of the entire predictive densities, and not just the probability assigned to the outcome that occurs. Overall, we find considerable heterogeneity in the performance of the surveyed densities at the individual level. However, it is hard to exploit this heterogeneity and improve aggregate performance by trimming poorly performing forecasters in real time. Relative to a set of simple benchmarks, density performance is somewhat better for GDP growth than for inflation, although in the former case it diminishes substantially with the forecast horizon. In addition, we report evidence of an improvement in the relative performance of expert densities during the recent period of macroeconomic volatility. However, our analysis also reveals clear evidence of overconfidence or neglected risks in expert probability assessments, as reflected in frequent occurrences of events which are assigned a zero probability. Copyright © 2014 John Wiley & Sons, Ltd.     

Overreaction in Survey Exchange Rate Forecasts

We use survey data on five bilateral exchange rates to provide empirical evidence of the fact that professional forecasters of foreign exchange rates behave irrationally, in the specific sense that they respond inaccurately to available information in the market when forming their predictions. In particular, we find systematic biases in the forecasts resulting in the overreaction of analysts to past information contained in the exchange rate dynamics: forecasters change their prediction more than it would be rational on the basis of past realized changes. In addition, forecasters are heterogeneous in their irrationality: low performers in previous periods show a more pronounced overreaction effect. This can be read as an indication of perpetration of past errors and continued inability to learn from the past. In the second part of the paper, we exploit the novel structure of our dataset, which consists of survey data extracted from the Bloomberg platform and readily available to anyone. This feature allows us to consider their own and others' past forecasts as part of the information set that analysts use in making their predictions. By using past forecasts as proxies for relevant macroeconomic variables, we find evidence that analysts fail to correctly process not only the information contained in the spot rate past dynamics but also the information in this broader set. We see this as confirmation of the existence of inefficiency and heterogeneity between low and high performers also when full information is available. Copyright © 2014 John Wiley & Sons, Ltd.     

Forecast Combination and Bayesian Model Averaging: A Prior Sensitivity Analysis

In this study we evaluate the forecast performance of model‐averaged forecasts based on the predictive likelihood carrying out a prior sensitivity analysis regarding Zellner's g prior. The main results are fourfold. First, the predictive likelihood does always better than the traditionally employed ‘marginal’ likelihood in settings where the true model is not part of the model space. Secondly, forecast accuracy as measured by the root mean square error (RMSE) is maximized for the median probability model. On the other hand, model averaging excels in predicting direction of changes. Lastly, g should be set according to Laud and Ibrahim (1995: Predictive model selection. Journal of the Royal Statistical Society B 57 : 247–262) with a hold‐out sample size of 25% to minimize the RMSE (median model) and 75% to optimize direction of change forecasts (model averaging). We finally apply the aforementioned recommendations to forecast the monthly industrial production output of six countries, beating for almost all countries the AR(1) benchmark model. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

浅谈电力DSM技术及其在中国的发展

主要介绍了电力需求方管理或需求侧管理(DSM)的发展、目的和技术,论述了实施DSM的效益以及DSM在我国的实施情况和前景。     

电刺激小脑顶核对大鼠心肌梗死后心脏神经再生的影响

探讨预先电刺激小脑顶核(FNS)对大鼠心肌梗死(MI)后心脏神经再生的干预作用。将90只Wistar大鼠随机分为:①MI组,结扎左冠状动脉前降支(LAD);②预先电刺激小脑顶核后再予以LAD结扎组(FNS MI组);③毁损小脑顶核后电刺激该部位,再行LAD结扎组(FNL FNS MI组)。各组又分MI后1,7,21d3个时间点。另设假手术组(Sham组)。应用免疫组织化学方法显示心脏组织胆碱乙酰转移酶(CHAT)和酪氨酸羟化酶(TH)。检测各时间点梗死区与非梗死区TH、CHAT阳性神经纤维分布密度,MI组与Sham组相比显著减少(P<0.01);FNS MI组较MI组显著增多(P<0.05);FNL FNS MI组与MI组比较无显著性差异(P>0.05)。因此,电刺激小脑顶核可增加梗死区和非梗死区心肌组织TH、CHAT染色阳性神经纤维密度,促进MI后心脏神经纤维再生。     

计价软件在工程计价教学中的应用

随着建筑行业对工程管理效率和精度要求的不断提高，计价软件已经成为预算人员必须掌握的工具之一。因而，在工程计价的教学中，应结合计价软件，让学生在理解综合单价由来的同时，掌握实际操作是如何把理论结合起来的。     

架空线路耐张杆塔上使用硅橡胶复合绝缘子设计探讨

硅橡胶复合绝缘子自上世纪九十年代开始，已经陆续广泛应用在高压送电线路杆塔上了，但是主要还是应用在直线杆塔上作为悬垂串使用。而对于耐张转角杆塔上的应用主要还是传统的瓷、玻璃绝缘子。本文通过作者的分析，希望对这个问题做更深一步的探讨。