Robust evaluation of fixed‐event forecast rationality

In this paper we introduce a new testing procedure for evaluating the rationality of fixed‐event forecasts based on a pseudo‐maximum likelihood estimator. The procedure is designed to be robust to departures in the normality assumption. A model is introduced to show that such departures are likely when forecasters experience a credibility loss when they make large changes to their forecasts. The test is illustrated using monthly fixed‐event forecasts produced by four UK institutions. Use of the robust test leads to the conclusion that certain forecasts are rational while use of the Gaussian‐based test implies that certain forecasts are irrational. The difference in the results is due to the nature of the underlying data. Copyright © 2001 John Wiley & Sons, Ltd.     

Ex-post and ex-ante prediction of unobserved economic time series: a case study

In several countries, some macro-economic variables are not observed frequently (e.g. quarterly) and economic authorities need estimates of these high-frequency figures to make econometric analyses or to follow closely the country's economic growth. Two problems are involved in this context. The first is to make these estimates after observing low-frequency values and some related indicators, and the second is to obtain predictions using just the observed indicators, i.e. before observing a new low-frequency figure. This paper gives a new optimal solution to the first problem, and solves the second using a recursive optimal approach. In the second situation, additionally, statistical tests are developed for detecting structural changes at current periods in the macro-economic variable involved. © 1998 John Wiley & Sons, Ltd.     

基于自热修正的SOI NMOSFETs热载流子注入效应寿命预测方法

自热效应SHE（self-heating effect）是SOI MOSFETs可靠性研究的关键问题之一.在热载流子注入HCI（hot carrier injection）应力下会导致自热效应加剧,低估器件工作寿命,使得寿命预测不准.本文提出了一种基于直流HCI应力下的0.18μmPD-SOINMOSFETs可靠性寿命预测方法.通过栅电阻法提取沟道中因自热效应产生的温度,采用自热修正后的衬底电流/漏电流比率模型预测PD-SOI NMOSFETs在正常工作电压下的寿命值,预测结果与未消除自热影响预测出的寿命值存在较大差异,说明自热修正在寿命预测中不可忽略,否则会低估器件的工作寿命.     

Political manoeuvrings as sources of measurement errors in forecasts

We test the extent to which political manoeuvrings can be the sources of measurement errors in forecasts. Our objective is to examine the forecast error based on a simple model in which we attempt to explain deviations between the March budget forecast and the November forecast, and deviations between the outcome and the March budget forecast in the UK. The analysis is based on forecasts made by the general government. We use the forecasts of the variables as alternatives to the outcomes. We also test for political spins in the GDP forecast updates and the GDP forecast errors. We find evidence of partisan and electoral effects in forecast updates and forecast errors. Copyright © 2005 John Wiley & Sons, Ltd.     

On estimation and prediction procedures for ar(1) models with power transformation

The power transformation of Box and Cox (1964) has been shown to be quite useful in short-term forecasting for the linear regression model with AR(1) dependence structure (see, for example, Lee and Lu, 1987, 1989). It is crucial to have good estimates of the power transformation and serial. correlation parameters, because they form the basis for estimating other parameters and predicting future observations. The prediction of future observations is the main focus of this paper. We propose to estimate these two parameters by minimizing the mean squared prediction errors. These estimates and the corresponding predictions compare favourably, via revs and simulated data, with those obtained by the maximum likelihood method. Similar results are also demonstrated in the repeated measurements setting.     

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

Gaussian processes for daily demand prediction in tourism planning

This study proposes Gaussian processes to forecast daily hotel occupancy at a city level. Unlike other studies in the tourism demand prediction literature, the hotel occupancy rate is predicted on a daily basis and 45 days ahead of time using online hotel room price data. A predictive framework is introduced that highlights feature extraction and selection of the independent variables. This approach shows that the dependence on internal hotel occupancy data can be removed by making use of a proxy measure for hotel occupancy rate at a city level. Six forecasting methods are investigated, including linear regression, autoregressive integrated moving average and recent machine learning methods. The results indicate that Gaussian processes offer the best tradeoff between accuracy and interpretation by providing prediction intervals in addition to point forecasts. It is shown how the proposed framework improves managerial decision making in tourism planning.     

上市公司期权激励公告的市场反应研究

在回顾期权激励相关研究的基础上,利用事件研究法对《上市公司股权激励管理办法》实施以来我国上市公司期权激励公告的市场反应进行了研究,并检验了不同市场对期权激励公告的反应是否相同.研究表明,市场对期权激励公告持积极态度,公告公司股票能获得比非公告公司股票更高的累积超额收益,且不同市场股票的CAR没有差异.     

Case study research in the social sciences

In this paper, we offer an introduction to case study research in the social sciences. We begin with a discussion of the definition of case study research. Next, we point to various purposes that case study research may serve in the social sciences and then turn to outline the main philosophical issues raised by case study research. Finally, we briefly present the papers in this special issue.     

Earthquake prediction,biological clocks,and the cold war psy-ops: Using animals as seismic sensors in the 1970s California

A familiar story of seismology is that of a small field originally focused on local studies of earthquakes through diverse disciplinary perspectives being transformed, in the second half of the twentieth century, into a highly specialized field focused on global studies of the earth's deep interior via sophisticated instruments and transnational networks of seismological stations. Against this backdrop, this essay offers a complementing account, highlighting the significance of local circumstances and disciplinary agendas that were contingent not only on transformations in the geophysical sciences but also on the concurrently changing biological sciences during the Cold War. Using examples of the studies of unusual animal behavior prior to earthquakes conducted under the auspices of the US Geological Survey on the West Coast of the United States in the 1970s, this essay examines a variety of motivations behind the attempts to bridge geophysics and biology. These examples illustrate the ways in which earthquake prediction became entangled with concerns over the use of seismological data, pioneering research on biological rhythms, and the troubled field of Cold War-driven military brain studies.