An Analysis of Trade Patterns and the Effects of the Real Exchange Rate Movements in East Asia

This article investigates the patterns of vertical specialization in trade among China, Japan and Korea, and the effects of real exchange rate fluctuations under a multistage production process. By extending the models of Yi (2003, 2010), we derive two distinct features of vertical specialization and test them using Time-Varying Parameter (TVP) VAR. We find that a positive shock to China’s final good consumption increases the intermediate goods trade between Korea and China, with expanding magnitude over time. In addition, the positive effect of a real exchange rate depreciation on intermediate goods trade is strengthened through the competitiveness-enhancing channel, with this effect being more pronouncing in Korea-China trade than in Korea-Japan trade.     

Explicit filters and supply chain design

Due to the complexity of present day supply chains it is important to select the simplest supply chain scheduling decision support system (DSS) which will determine and place orders satisfactorily. We propose to use a generic design framework, termed the explicit filter methodology, to achieve this objective. In doing so we compare the explicit filter approach to the implicit filter approach utilised in previous OR research the latter focusing on minimising a cost function. Although the eventual results may well be similar with both approaches it is much clearer to the designer, both why and how, an ordering system will reduce the Bullwhip effect via the explicit filter approach. The “explicit filter” approach produces a range of DSS designs corresponding to best practice. These may be “mixed and matched” to generate a number of competitive delivery pipelines to suit the specific business scenario.     

Estimation methods for stochastic volatility models: a survey

Abstract.  Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index.     

EMI滤波器的设计

文章从建立EMI滤波器的共模、差模噪声源等效电路及电路模型入手,进而探讨了EMI滤波器的设计方法及其在实际应用的结构和结构参数的选择问题。     

Testing the significance and the non-linearity of the Phillips trade-off in the Euro Area

This paper tests the significance and the non-linearity of the Phillips trade-off in the aggregate Euro Area, in an unobserved components model of stochastic NAIRU and trend output featuring the Phillips equation and the Okun law as main identifying equations, with quarterly data for 1970:I-2002:III. The Phillips curve turns out to be linear and its trade-off statistically significant, while non-linearity shows up in the Okun relation. The results prove to be robust to alternative lag length structures of the model, and to alternative non-linear functional forms. The trend-cycle decompositions estimated with the model capture the main features of the Euro Area’s recent macroeconomic record.First version received: 1 September 2003 / Final version received: June 2004CEMPRE - Centro de Estudos Macroeconómicos e Previsão - is supported by the Fundação para a Ciência e a Tecnologia, Portugal, through the Programa Operacional Ciência, Tecnologia e Inovação (POCTI) of the Quadro Comunitário de Apoio III, which is financed by FEDER and Portuguese funds.We thank comments on earlier versions by Fabio Canova, Miguel St Aubyn, Alvaro Almeida, Pete Richardson, Kevin Ross, and two anonymous referees. We acknowledge James D. Hamilton’s help with the confidence bands. The usual disclaimer applies.     

Seasonality and Markov switching in an unobserved component time series model

It is generally acknowledged that the growth rate of output, the seasonal pattern, and the business cycle are best estimated simultaneously. To achieve this, we develop an unobserved component time series model for seasonally unadjusted US GDP. Our model incorporates a Markov switching regime to produce periods of expansion and recession, both of which are characterized by different underlying growth rates. Although both growth rates are time-varying, they are assumed to be cointegrated. The analysis is Bayesian, which fully accounts for all sources of uncertainty. Comparison with results from a similar model for seasonally adjusted data indicates that the seasonal adjustment of the data significantly alters several aspects of the full model. First Version Received: January 2001/Final Version Received: February 2002 Send offprint requests to: Rob Luginbuhl?Correspondence to: Rob Luginbuhl     

Forecasting UK house prices: A time varying coefficient approach

Previous studies of UK house prices, developed from the demand and supply ofhousing or from the asset market approach have been poor in terms of robustness and ex-post forecasting ability. The UK housing market has suffered a number of structural changes, particularly since the early 1980s with substantial house price increases, financial market deregulation and the removal of mortgage market constraints through competition. Consequently, models which assume that the underlying data-generating process is stable and apply constant parameter techniques tend to suffer in terms of parameter instability. This article uses the Time Varying Coefficient (TVC) methodology where the underlying data-generating process in the UK housing market is treated as unstable. The estimation results of the TVC regression of UK house prices is compared with those obtained from three alternative constant parameter regressions. Comparisons of forecasting performance suggest the TVC regression out-performs forecasts from an Error Correction Mechanism (ECM), Vector Autoregressive (VAR) and an Autoregressive Time Series regression.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

节能省地型住宅发展评价指标体系研究

借鉴可持续发展评价指标体系的设计方法,结合城市住宅发展的特点,通过定性与定量分析相结合,提出了节能省地型住宅发展评价指标体系构建方法;建立了多级递阶层次结构式的评价指标体系,为节能省地型住宅发展的进一步定量研究奠定了坚实的基础,具有非常重要的研究价值和实践意义。     

北斗/CDMA组合导航数据融合及其在军事物流中的应用研究

提出了一种新的组合导航定位技术-北斗/CDMA导航定位,进一步研究了如何利用数据融合技术提高定位精度与可靠性。设计了一种简化的联邦卡尔曼滤波器并给出了相应的滤波算法流程。最后提出了北斗/CDMA组合导航定位技术在军事物流监控调度系统中的应用解决方案。