Macroeconomic forecasting using approximate factor models with outliers

In this paper we consider estimating an approximate factor model in which candidate predictors are subject to sharp spikes such as outliers or jumps. Given that these sharp spikes are assumed to be rare, we formulate the estimation problem as a penalized least squares problem by imposing a norm penalty function on those sharp spikes. Such a formulation allows us to disentangle the sharp spikes from the common factors and estimate them simultaneously. Numerical values of the estimates can be obtained by solving a principal component analysis (PCA) problem and a one-dimensional shrinkage estimation problem iteratively. In addition, it is easy to incorporate methods for selecting the number of common factors in the iterations. We compare our method with PCA by conducting simulation experiments in order to examine their finite-sample performances. We also apply our method to the prediction of important macroeconomic indicators in the U.S., and find that it can deliver performances that are comparable to those of the PCA method.     

Rational bubbles and non-risk neutral investors in Japan

This paper presents a sufficient condition for not observing rational bubbles in real stock prices when investors are not risk neutral and both the real interest rate and the risk premium are time varying. If the risk premium and the real interest rate are stationary, the stationarity of the first differences of real stock prices is a sufficient condition for the absence of rational bubbles. Testing this condition with data on Japanese stock prices, we find that the hypothesis that rational bubbles existed is rejected.     

论述全面质量管理在高校科研管理中的重要性

本文通过分析传统的高校科研管理存在的若干问题,并从内部环境和外部压力两大方面指出优化高校科研管理和构建高校科研的全面质量管理体系的迫切性和必要性,最后,阐述了在高校科研工作方面推行全面质量管理的重大意义。     

The Time Series Properties of Financial Ratios: Lev Revisited

This paper re‐evaluates the time series properties of financial ratios. It presents new empirical analysis which explicitly allows for the possibility that financial ratios can be characterized as non‐linear mean‐reverting processes. Financial ratios are widely employed as explanatory variables in accounting and finance research with applications ranging from the determinants of auditors' compensation to explaining firms' investment decisions. An implicit assumption in this empirical work is that the ratios are stationary so that the postulated models can be estimated by classical regression methods. However, recent empirical work on the time series properties of corporate financial ratios has reported that the level of the majority of ratios is described by non‐stationary, I (1), integrated processes and that the ratio differences are parsimoniously described by random walks. We hypothesize that financial ratios may follow a random walk near their target level, but that the more distant a ratio is from target, the more likely the firm is to take remedial action to bring it back towards target. This behavior will result in a significant size distortion of the conventional stationarity tests and lead to frequent non‐rejection of the null hypothesis of non‐stationarity, a finding which undermines the use of these ratios as reliable conditioning variables for the explanation of firms' decisions.     

Testing Gaussianity and Linearity of Japanese Stock Returns

In this article, we first investigate the Gaussianity of Japanese stock return time series (214 daily, 18 weekly) by the Gaussianity test proposed by Kariya, Tsay, Terui and Li (1994) comprehensively and consistently. And it is observed that all the series are not Gaussian when the 6th order moment structures are taken into account. Up to the 4th order moments there are some series which are compatible with the Gaussianity. Secondly, we apply five well-known nonlinearity tests for stationary time series to the data set and examine the specific nonlinearity of the series. Some series strongly exhibit the specific types of nonlinearity. Typically the Nikkei daily index shows the TAR (Threshold Autoregressive) type nonlinearity. Comparing daily return series with weekly series, it is also shown that a central limit effect is working on the weekly stock returns, where daily information is accumulated over a week, in the sense that weekly returns are relatively closer to Gaussian.     

Urban sprawl and social interaction potential: an empirical analysis of large metropolitan regions in the United States

This paper investigates the impact of urban spatial structure on the opportunities for people to participate in face-to-face activities. We make use of the Social Interaction Potential (SIP) metric, a tool to measure the average level of opportunity for people to engage in face-to-face activities given some basic constraints on their daily mobility patterns. Generally, this opportunity is a reflection of whether the urban spatial structure – a term that broadly applies to the spatial arrangement of land-uses and the interactions between them – constrains or permits the ability for potential activity partners to be at the same place and time. In this paper, the SIP metric is applied to 42 metropolitan regions in the United States with populations over 1,000,000 people. These measurements are regressed against a set of indicators of urban sprawl to expose the relationship between spatial structure and SIP. The indicators are generated by a factor analysis of a large set of variables describing the scale, centrality and dispersion of land-uses in addition to several other structural and infrastructure-related variables. Cluster analysis is also used to organize the regions into similar groupings with respect to their structural characteristics and the level of SIP they provide. The findings indicate that social interaction potential is hampered by decentralization, fragmentation, and longer commutes in the largest metropolitan regions in the country. Interestingly, the negative effect of decentralization on SIP Efficiency is found to be nearly ten times stronger than that of fragmentation and nearly 20 times stronger than the effect of mean commuting duration.     

A time varying parameter approach to the Chinese aggregate consumption function

China experienced a number of economic, political and social upheavals in the pre-reform period, together with a gradual transformation from a centrally-planned to a market oriented economy in the post-reform period. Given this background of extensive change, a time varying parameter (TVP) consumption model for non-durables is developed in order to determine the resulting changes in consumer behaviour caused by both observable and unobservable factors. The parameters of interest are the short and long run marginal propensities to consume (MPC) and the long run average propensity to consume (APC). The model is based on Friedman's permanent income hypothesis (PIH) and estimated using the Kalman filter algorithm. The empirical results suggest that the TVP model is a good representation of the changes in Chinese consumer behaviour over time. In terms of forecasting, the TVP model generally outperforms a number of alternative models.     

燃料气压缩机在低气量和压力下运行的研究和应用

主要介绍了燃料气压缩机是为燃气轮机提供一定压力和温度的燃料气的动力设备。时常由于作为临时原料气的燃料气入口压力低造成燃料气压缩机由于排气高温而停机。这时燃机也因为缺乏燃料而停机。通过采用两台燃料气压缩机串机运行、并机运行和单独运行时打开补气阀补气的措施，最终解决了燃机的供气问题。     

Modeling Marketing Dynamics by Time Series Econometrics

This paper argues that time-series econometrics provides valuable tools and opens exciting research opportunities to marketing researchers. It allows marketing researchers to advance traditional modeling and estimation approaches by incorporating dynamic processes to answer new important research questions. The authors discuss the challenges facing time-series modelers in marketing, provide an overview of recent methodological developments and several applications, and highlight fruitful areas for future research. This discussion is based on the First Annual Conference on Modeling Marketing Dynamics by Time Series Econometrics at the Tuck School of Business at Dartmouth, Hanover, New Hampshire, USA on September 16–17, 2004.Insights from the First Annual Conference, Tuck School of Business at DartmouthThis revised version was published online in May 2005 with a corrected cover date.     

2004年我国税收与经济增长的协调关系

2004年我国税收总收入比上年增长25．7％。增收额和增长幅度均实现历史性新突破。税收收入快速增长，使国家财力进一步增强，为支持经济社会发展作出了积极贡献。但与此同时人们对税收连年超经济增长，也存在不少疑虑。本文从经济总量、产业结构角度，并运用时间序列模型等，讨论分析了税收与经济增长的协调性及关系。