Forecast quality improvement with Action Research: A success story at PharmaCo

There is a gap in the forecasting research surrounding the theory of integrating and improving forecasting in practice. The number of academically affiliated consultancies and knowledge transfer projects that there are around, due to a need for improvements in forecast quality, would suggest that many interventions and actions are taking place. However, the problems that surround practitioner understanding, learning and usage are rarely documented. This article takes the first step toward trying to rectify this situation by using the specific case study of a fully engaged company. A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial savings, enhanced communication and improved working practices.     

A note on forecasting international tourism demand in Spain

This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.     

Evaluating FOMC forecasts

Monetary policy outcomes have improved since the early 1980s. One factor contributing to the improvement is that Federal Reserve policymakers began reporting economic forecasts to Congress in 1979. These forecasts indicate what the Federal Open Market Committee (FOMC) members think will be the likely consequence of their policies. We evaluate the accuracy of the FOMC forecasts relative to private sector forecasts, the forecasts of the Research Staff at the Board of Governors, and a naïve alternative. We find that the FOMC output forecasts were better than the naïve model and at least as good as those of the private sector and the Fed staff. The FOMC inflation forecasts were more accurate than the private sector forecasts and the naïve model; for the period ending in 1996, however, they were not as accurate as Fed staff inflation forecasts.     

Terrorism activities and long-term annual management forecasts

We study the effects of terrorist attacks on firms’ long-term annual management earnings forecasts bias. We find that the managers of firms located closer to the epicenters of attacks are more likely to issue optimistic long-term annual earnings forecasts relative to the managers of a control group of unaffected firms. The exposure effect is stronger for more severe terrorist events, and firms with more uncertain fundamentals and less geographic diversification. In addition, we document that managers’ forecast optimism intensifies for firms with stronger negative stock market reaction to the terrorist event, for CEOs with higher ability and for companies that are more likely to issue equity or engage in acquisitions following the terrorist event. Overall, our results are consistent with the idea that long-term annual earnings forecasts are used by managers to counterbalance the short-term pessimistic response to terrorist attacks.     

通货膨胀实时预测及菲利普斯曲线的适用性

本文从实时分析的视角,基于多种退势方法的产出缺口最终估计、准最终估计和实时估计序列,分别构建了四类预测模型对我国通货膨胀率进行预测,分析了产出缺口修正效应和滞后阶数变化效应对通胀预测的影响,并进一步考察了产出缺口在通胀预测中的作用及菲利普斯曲线在通胀预测中的适用性。研究结论表明,通胀率的实时预测效果要明显比基于最终数据的差,其中滞后阶数变化效应对实时预测精度的影响大于产出缺口修正效应;尤为重要的是,尽管在最终数据的预测分析中,产出缺口的引入能够提高通胀率的预测精度,但是在实时预测中,产出缺口没有提供有价值的信息,因此"产出—通胀"型菲利普斯曲线在我国通胀实时预测中并不适用。     

Macroeconomic forecasting using structural factor analysis

The use of a small number of underlying factors to summarize the information from a much larger set of information variables is one of the new frontiers in forecasting. In prior work, the estimated factors have not usually had a structural interpretation and the factors have not been chosen on a theoretical basis. In this paper we propose several variants of a general structural factor forecasting model, and use these to forecast certain key macroeconomic variables. We make the choice of factors more structurally meaningful by estimating factors from subsets of information variables, where these variables can be assigned to subsets on the basis of economic theory. We compare the forecasting performance of the structural factor forecasting model with that of a univariate AR model, a standard VAR model, and some non-structural factor forecasting models. The results suggest that our structural factor forecasting model performs significantly better in forecasting real activity variables, especially at short horizons.     

倾斜摄影测量中影响模型精度的因素分析

目前,倾斜摄影测量作为一种新技术,经过不断的探索、应用和发展,已开始在测绘行业中大显身手,并取得了不小的成绩。通过三维模型进行的矢量数据采集,其矢量精度完全依赖于三维模型精度。论文以实践经验为基础,定性地分析了在航空摄影、像控测量、模型生产三阶段中,影响模型精度的因素,希望对三维模型的生产起到一定的指导作用。     

Seasonal decomposition and forecasting of telecommunication data: A comparative case study

In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University.     

The Delphi method, impeachment and terrorism: Accuracies of short-range forecasts for volatile world events

Two experiments examined the effects of iterated polling and feedback on prediction accuracy for volatile world events using the Delphi paradigm. In both experiments, participants predicted rapidly changing geopolitical events. The first experiment occurred during the litigation surrounding the Clinton/Lewinsky affair in 1998. Results indicated that feedback improved individual and group accuracy for predictions of whether an event would occur. These types of predictions derived from group consensus were approximately 90% accurate, which was significantly higher than the average individual participant's accuracy. Neither polling nor feedback had much effect on time course predictions. The second experiment occurred during the American military action against the Taliban regime in Afghanistan in 2001. In Experiment 2, participants were polled three times to determine if increasing the number of iterated polls would improve Delphi accuracy. The results showed that accuracy improved from the first to the second poll but not from the second to the third. The groups predicted whether these scenarios would occur with approximately 75% accuracy, which was significantly higher than the accuracy of any individual participant. Once again, the Delphi procedure did not enhance time course predictions in Experiment 2.     

Capitalized intangibles and financial analysts

We examine whether firms that capitalize a higher proportion of their underlying intangible assets have higher analyst following, lower dispersion of analysts’ earnings forecasts and more accurate earnings forecasts relative to firms that capitalize a lower proportion. Under Australian generally accepted accounting principles, capitalization of intangible assets has become increasingly ‘routine’ since the late 1980s. It is predicted that this experience leads Australian analysts to expect firms with relatively more certain intangible investments to signal this fact by capitalizing intangible assets. Our results are consistent with this. We find that capitalization of intangible assets is associated with higher analyst following and lower absolute earnings forecast error for firms with a stock of underlying intangible assets. Our tests suggest a weaker association between capitalization and lower earnings forecast dispersion. We conclude that there are benefits for analysts, for management to have the option to capitalize intangible assets. These findings suggest that IAS 38 Intangible Assets and AASB 138 Intangible Assets reduce the usefulness of financial statements.